Cardiovascular disease risk factors in congenital heart disease survivors are associated with heart failure.

BACKGROUND: Despite advances in treatment and survival, individuals with congenital heart defects (CHD) have a higher risk of heart failure (HF) compared to the general population. OBJECTIVE: To evaluate comorbidities associated with HF in patients with CHD with a goal of identifying potentially modifiable risk factors that may reduce HF-associated morbidity and mortality. METHODS: Five surveillance sites in the United States linked population-based healthcare data and vital records. Individuals with an ICD-9-CM code for CHD aged 11-64 years were included and were stratified by presence of HF diagnosis code. Prevalence of death and cardiovascular risk factors based on diagnosis codes were compared by HF status using log-linear regression. RESULTS: A total of 25,343 individuals met inclusion/exclusion criteria. HF was documented for 2.2% of adolescents and 12.9% of adults with CHD. Adolescents and adults with HF had a higher mortality than those without HF. In both age groups, HF was positively associated with coronary artery disease, hypertension, obesity, diabetes, and increased healthcare utilization compared to those without HF. CONCLUSIONS: Within this population-based cohort, over 1 in 50 adolescents and 1 in 8 adults with CHD had HF, which was associated with increased mortality. Modifiable cardiovascular comorbidities were associated with HF. IMPACT: Five sites in the United States linked population-based healthcare data and vital records to establish surveillance network for identifying the factors which influence congenital heart disease (CHD) outcomes. Survivors of CHD frequently develop heart failure across the lifespan. Over 1 in 50 adolescent and 1 in 8 adult survivors of CHD have heart failure which is associated with increased mortality compared to CHD survivors without heart failure. Heart failure development is associated with potentially modifiable cardiovascular risk factors such as hypertension, coronary artery disease, and diabetes. Controlling modifiable cardiovascular risk factors may serve to lower the risk of heart failure and mortality in survivors of congenital heart disease of all ages.

Child Age at Time of First Maternal Concern and Time to Services Among Children with Autism Spectrum Disorder.

OBJECTIVE: Early treatment of autism spectrum disorder (ASD) can improve developmental outcomes. Children with ASD from minority families often receive services later. We explored factors related to child's age at time of mother's first concerns about child's development and subsequent time to service initiation among children with ASD. METHODS: Analysis included 759 preschool-age children classified with ASD based on comprehensive evaluations. Factors associated with retrospectively reported child age at time of first maternal concern and subsequent time to service initiation were investigated using multiple linear regression and Cox proportional hazards. RESULTS: Earlier maternal concern was associated with multiparity, ≥1 child chronic condition, externalizing behaviors, and younger gestational age, but not race/ethnicity. Time to service initiation was longer for children of non-Latino Black or other than Black or White race and higher developmental level and shorter for children with ≥1 chronic condition and older child age at first maternal concern. CONCLUSION: Parity, gestational age, and child health and behavior were associated with child age at first maternal concern. Knowledge of child development in multiparous mothers may allow them to recognize potential concerns earlier, suggesting that first time parents may benefit from enhanced education about normal development. Race/ethnicity was not associated with child's age when mothers recognized potential developmental problems; hence, it is unlikely that awareness of ASD symptoms causes racial/ethnic disparities in initiation of services. Delays in time to service initiation among children from racial/ethnic minority groups highlight the need to improve their access to services as soon as developmental concerns are recognized.

Using electronic health records to enhance surveillance of diabetes in children, adolescents and young adults: a study protocol for the DiCAYA Network.

INTRODUCTION: Traditional survey-based surveillance is costly, limited in its ability to distinguish diabetes types and time-consuming, resulting in reporting delays. The Diabetes in Children, Adolescents and Young Adults (DiCAYA) Network seeks to advance diabetes surveillance efforts in youth and young adults through the use of large-volume electronic health record (EHR) data. The network has two primary aims, namely: (1) to refine and validate EHR-based computable phenotype algorithms for accurate identification of type 1 and type 2 diabetes among youth and young adults and (2) to estimate the incidence and prevalence of type 1 and type 2 diabetes among youth and young adults and trends therein. The network aims to augment diabetes surveillance capacity in the USA and assess performance of EHR-based surveillance. This paper describes the DiCAYA Network and how these aims will be achieved. METHODS AND ANALYSIS: The DiCAYA Network is spread across eight geographically diverse US-based centres and a coordinating centre. Three centres conduct diabetes surveillance in youth aged 0-17 years only (component A), three centres conduct surveillance in young adults aged 18-44 years only (component B) and two centres conduct surveillance in components A and B. The network will assess the validity of computable phenotype definitions to determine diabetes status and type based on sensitivity, specificity, positive predictive value and negative predictive value of the phenotypes against the gold standard of manually abstracted medical charts. Prevalence and incidence rates will be presented as unadjusted estimates and as race/ethnicity, sex and age-adjusted estimates using Poisson regression. ETHICS AND DISSEMINATION: The DiCAYA Network is well positioned to advance diabetes surveillance methods. The network will disseminate EHR-based surveillance methodology that can be broadly adopted and will report diabetes prevalence and incidence for key demographic subgroups of youth and young adults in a large set of regions across the USA.

Maternal psychosocial stress during pregnancy and offspring neurobehavioral outcomes during early childhood in the Healthy Start Study.

PURPOSE: We evaluate singular and combined effects of prenatal maternal depression and stress on early childhood neurobehavioral outcomes among 536 mother-child pairs. METHODS: First, we used multivariable linear regression to investigate associations of women's Edinburgh Postnatal Depression Scale (EPDS) score and Perceived Stress Scale (PSS) score, separately, with offspring Child Behavior Checklist score. Next, to assess the combined effect of EPDS and PSS, we dichotomized each score at the fourth versus first to third quartiles and created a four-level variable comprising combinations of high and low depression and stress. Across all models, we accounted for household chaos, hubbub, and order scale (CHAOS) score, an indicator of the household environment associated with offspring behavioral outcomes. RESULTS: Each one-unit increment in maternal EPDS and PSS scores corresponded with 0.75 (95% CI: 0.53, 0.96) and 0.72 (95% CI: 0.48, 0.95) units higher offspring total problems T-score, respectively. Children of women with high EPDS and PSS had highest T-scores for total problems. All associations remained materially unchanged after adjustment for CHAOS score. CONCLUSIONS: Prenatal maternal depression and stress is associated with worse neurobehavioral outcomes among offspring, with the most unfavorable outcomes among children whose mothers had high scores for both EPDS and PSS.

Evaluating the Discriminatory Ability of the Sickle Cell Data Collection Program's Administrative Claims Case Definition in Identifying Adults With Sickle Cell Disease: Validation Study.

BACKGROUND: Sickle cell disease (SCD) was first recognized in 1910 and identified as a genetic condition in 1949. However, there is not a universal clinical registry that can be used currently to estimate its prevalence. The Sickle Cell Data Collection (SCDC) program, funded by the Centers for Disease Control and Prevention, funds state-level grantees to compile data within their states from various sources including administrative claims to identify individuals with SCD. The performance of the SCDC administrative claims case definition has been validated in a pediatric population with SCD, but it has not been tested in adults. OBJECTIVE: The objective of our study is to evaluate the discriminatory ability of the SCDC administrative claims case definition to accurately identify adults with SCD using Medicaid insurance claims data. METHODS: Our study used Medicaid claims data in combination with hospital-based medical record data from the Alabama, Georgia, and Wisconsin SCDC programs to identify individuals aged 18 years or older meeting the SCDC administrative claims case definition. In order to validate this definition, our study included only those individuals who were identified in both Medicaid's and the partnering clinical institution's records. We used clinical laboratory tests and diagnostic algorithms to determine the true SCD status of this subset of patients. Positive predictive values (PPV) are reported overall and by state under several scenarios. RESULTS: There were 1219 individuals (354 from Alabama and 865 from Georgia) who were identified through a 5-year time period. The 5-year time period yielded a PPV of 88.4% (91% for data from Alabama and 87% for data from Georgia), when only using data with laboratory-confirmed (gold standard) cases as true positives. With a narrower time period (3-year period) and data from 3 states (Alabama, Georgia, and Wisconsin), a total of 1432 individuals from these states were included in our study. The overall 3-year PPV was 89.4% (92%, 93%, and 81% for data from Alabama, Georgia, and Wisconsin, respectively) when only considering laboratory-confirmed cases as true cases. CONCLUSIONS: Adults identified as having SCD from administrative claims data based on the SCDC case definition have a high probability of truly having the disease, especially if those hospitals have active SCD programs. Administrative claims are thus a valuable data source to identify adults with SCD in a state and understand their epidemiology and health care service usage.

Longitudinal Assessment of Multimorbidity Medication Patterns among Smokers in the COPDGene Cohort.

Background and objectives: Chronic obstructive pulmonary disease (COPD) is usually comorbid with other chronic diseases. We aimed to assess the multimorbidity medication patterns and explore if the patterns are similar for phase 1 (P1) and 5-year follow-up phase 2 (P2) in the COPDGene cohort. Materials and Methods: A total of 5564 out of 10,198 smokers from the COPDGene cohort who completed 2 visits, P1 and P2 visits, with complete medication use history were included in the study. We conducted latent class analysis (LCA) among the 27 categories of chronic disease medications, excluding COPD treatments and cancer medications at P1 and P2 separately. The best number of LCA classes was determined through both statistical fit and interpretation of the patterns. Results: We found four classes of medication patterns at both phases. LCA showed that both phases shared similar characteristics in their medication patterns: LC0: low medication; LC1: hypertension (HTN) or cardiovascular disease (CVD)+high cholesterol (Hychol) medication predominant; LC2: HTN/CVD+type 2 diabetes (T2D) +Hychol medication predominant; LC3: Hychol medication predominant. Conclusions: We found similar multimorbidity medication patterns among smokers at P1 and P2 in the COPDGene cohort, which provides an understanding of how multimorbidity medication clustered and how different chronic diseases combine in smokers.

Genome-wide analysis of oxylipins and oxylipin profiles in a pediatric population.

Background: Oxylipins are inflammatory biomarkers derived from omega-3 and-6 fatty acids implicated in inflammatory diseases but have not been studied in a genome-wide association study (GWAS). The aim of this study was to identify genetic loci associated with oxylipins and oxylipin profiles to identify biologic pathways and therapeutic targets for oxylipins. Methods: We conducted a GWAS of plasma oxylipins in 316 participants in the Diabetes Autoimmunity Study in the Young (DAISY). DNA samples were genotyped using the TEDDY-T1D Exome array, and additional variants were imputed using the Trans-Omics for Precision Medicine (TOPMed) multi-ancestry reference panel. Principal components analysis of 36 plasma oxylipins was used to capture oxylipin profiles. PC1 represented linoleic acid (LA)- and alpha-linolenic acid (ALA)-related oxylipins, and PC2 represented arachidonic acid (ARA)-related oxylipins. Oxylipin PC1, PC2, and the top five loading oxylipins from each PC were used as outcomes in the GWAS (genome-wide significance: p < 5×10-8). Results: The SNP rs143070873 was associated with (p < 5×10-8) the LA-related oxylipin 9-HODE, and rs6444933 (downstream of CLDN11) was associated with the LA-related oxylipin 13 S-HODE. A locus between MIR1302-7 and LOC100131146, rs10118380 and an intronic variant in TRPM3 were associated with the ARA-related oxylipin 11-HETE. These loci are involved in inflammatory signaling cascades and interact with PLA2, an initial step to oxylipin biosynthesis. Conclusion: Genetic loci involved in inflammation and oxylipin metabolism are associated with oxylipin levels.

An Oxylipin-Related Nutrient Pattern and Risk of Type 1 Diabetes in the Diabetes Autoimmunity Study in the Young (DAISY).

Oxylipins, pro-inflammatory and pro-resolving lipid mediators, are associated with the risk of type 1 diabetes (T1D) and may be influenced by diet. This study aimed to develop a nutrient pattern related to oxylipin profiles and test their associations with the risk of T1D among youth. The nutrient patterns were developed with a reduced rank regression in a nested case-control study (n = 335) within the Diabetes Autoimmunity Study in the Young (DAISY), a longitudinal cohort of children at risk of T1D. The oxylipin profiles (adjusted for genetic predictors) were the response variables. The nutrient patterns were tested in the case-control study (n = 69 T1D cases, 69 controls), then validated in the DAISY cohort using a joint Cox proportional hazards model (n = 1933, including 81 T1D cases). The first nutrient pattern (NP1) was characterized by low beta cryptoxanthin, flavanone, vitamin C, total sugars and iron, and high lycopene, anthocyanidins, linoleic acid and sodium. After adjusting for T1D family history, the HLA genotype, sex and race/ethnicity, NP1 was associated with a lower risk of T1D in the nested case-control study (OR: 0.44, p = 0.0126). NP1 was not associated with the risk of T1D (HR: 0.54, p-value = 0.1829) in the full DAISY cohort. Future studies are needed to confirm the nested case-control findings and investigate the modifiable factors for oxylipins.

Health Care Usage Among Adolescents With Congenital Heart Defects at 5 Sites in the United States, 2011 to 2013.

Background We sought to characterize health care usage for adolescents with congenital heart defects (CHDs) using population-based multisite surveillance data. Methods and Results Adolescents aged 11 to 18 years with ≥1 CHD-related diagnosis code and residing in 5 US sites were identified in clinical and administrative data sources for the years 2011 to 2013. Sites linked data on all inpatient, emergency department (ED), and outpatient visits. Multivariable log-binomial regression models including age, sex, unweighted Charlson comorbidity index, CHD severity, cardiology visits, and insurance status, were used to identify associations with inpatient, ED, and outpatient visits. Of 9626 eligible adolescents, 26.4% (n=2543) had severe CHDs and 21.4% had Charlson comorbidity index >0. At least 1 inpatient, ED, or outpatient visit was reported for 21%, 25%, and 96% of cases, respectively. Cardiology visits, cardiac imaging, cardiac procedures, and vascular procedures were reported for 38%, 73%, 10%, and 5% of cases, respectively. Inpatient, ED, and outpatient visits were consistently higher for adolescents with severe CHDs compared with nonsevere CHDs. Adolescents with severe and nonsevere CHDs had higher health care usage compared with the 2011 to 2013 general adolescent US population. Adolescents with severe CHDs versus nonsevere CHDs were twice as likely to have at least 1 inpatient visit when Charlson comorbidity index was low (Charlson comorbidity index =0). Adolescents with CHDs and public insurance, compared with private insurance, were more likely to have inpatient (adjusted prevalence ratio, 1.5 [95% CI, 1.3-1.7]) and ED (adjusted prevalence ratio, 1.6 [95% CI, 1.4-1.7]) visits. Conclusions High resource usage by adolescents with CHDs indicates a substantial burden of disease, especially with public insurance, severe CHDs, and more comorbidities.

A process to deduplicate individuals for regional chronic disease prevalence estimates using a distributed data network of electronic health records.

Introduction: Learning health systems can help estimate chronic disease prevalence through distributed data networks (DDNs). Concerns remain about bias introduced to DDN prevalence estimates when individuals seeking care across systems are counted multiple times. This paper describes a process to deduplicate individuals for DDN prevalence estimates. Methods: We operationalized a two-step deduplication process, leveraging health information exchange (HIE)-assigned network identifiers, within the Colorado Health Observation Regional Data Service (CHORDS) DDN. We generated prevalence estimates for type 1 and type 2 diabetes among pediatric patients (0-17 years) with at least one 2017 encounter in one of two geographically-proximate DDN partners. We assessed the extent of cross-system duplication and its effect on prevalence estimates. Results: We identified 218 437 unique pediatric patients seen across systems during 2017, including 7628 (3.5%) seen in both. We found no measurable difference in prevalence after deduplication. The number of cases we identified differed slightly by data reconciliation strategy. Concordance of linked patients' demographic attributes varied by attribute. Conclusions: We implemented an HIE-dependent, extensible process that deduplicates individuals for less biased prevalence estimates in a DDN. Our null pilot findings have limited generalizability. Overlap was small and likely insufficient to influence prevalence estimates. Other factors, including the number and size of partners, the matching algorithm, and the electronic phenotype may influence the degree of deduplication bias. Additional use cases may help improve understanding of duplication bias and reveal other principles and insights. This study informed how DDNs could support learning health systems' response to public health challenges and improve regional health.

Fetal Exposure to Cannabis and Childhood Metabolic Outcomes: The Healthy Start Study.

OBJECTIVE: To assess the impact of fetal exposure to cannabis on adiposity and glucose-insulin traits in early life. RESEARCH DESIGN AND METHODS: We leveraged a subsample of 103 mother-child pairs from Healthy Start, an ethnically diverse Colorado-based cohort. Twelve cannabinoids/metabolites of cannabis (including Δ9-tetrahydrocannabinol and cannabidiol) were measured in maternal urine collected at ~27 weeks' gestation. Fetal exposure to cannabis was dichotomized as exposed (any cannabinoid > limit of detection [LOD]) and not exposed (all cannabinoids < LOD). Fat mass and fat-free mass were measured via air displacement plethysmography at follow-up (mean age: 4.7 years). Glucose and insulin were obtained after an overnight fast. Generalized linear models estimated the associations between fetal exposure to cannabis with adiposity measures (fat mass [kg], fat-free mass [kg], adiposity [fat mass percentage], body mass index [BMI], and BMI z-scores) and metabolic measures (glucose [mg/dL], insulin [uIU/mL], and homeostatic model assessment of insulin resistance [HOMA-IR]). RESULTS: Approximately 15% of the women had detectable levels of any cannabinoid, indicating fetal exposure to cannabis. Exposed offspring had higher fat mass (1.0 kg; 95% CI, 0.3-1.7), fat-free mass (1.2 kg; 95% CI, 0.4-2.0), adiposity (2.6%; 95% CI, 0.1-5.2), and fasting glucose (5.6 mg/dL; 95% CI, 0.8-10.3) compared with nonexposed offspring. No associations were found with fasting insulin (in the fully adjusted model), HOMA-IR, BMI, or BMI z-scores. CONCLUSIONS: We provide novel evidence to suggest an association between fetal exposure to cannabis with increased adiposity and fasting glucose in childhood, a finding that should be validated in other cohorts.

Features that best define the heterogeneity and homogeneity of autism in preschool-age children: A multisite case-control analysis replicated across two independent samples.

The heterogeneous nature of children with symptoms of autism spectrum disorder (ASD) makes it difficult to identify risk factors and effective treatment options. We sought to identify behavioral and developmental features that best define the heterogeneity and homogeneity in 2-5-year-old children classified with ASD and subthreshold ASD characteristics. Children were enrolled in a multisite case-control study of ASD. Detailed behavioral and developmental data were gathered by maternal telephone interview, parent-administered questionnaires, child cognitive evaluation, and ASD diagnostic measures. Participants with a positive ASD screen score or prior ASD diagnosis were referred for comprehensive evaluation. Children in the ASD group met study criteria based on this evaluation; children who did not meet study criteria were categorized as having subthreshold ASD characteristics. There were 1480 children classified as ASD (81.6% boys) and 594 children classified as having subthreshold ASD characteristics (70.2% boys) in the sample. Factors associated with dysregulation (e.g., aggression, anxiety/depression, sleep problems) followed by developmental abilities (e.g., expressive and receptive language skills) most contributed to heterogeneity in both groups of children. Atypical sensory response contributed to homogeneity in children classified as ASD but not those with subthreshold characteristics. These findings suggest that dysregulation and developmental abilities are clinical features that can impact functioning in children with ASD and other DD, and that documenting these features in pediatric records may help meet the needs of the individual child. Sensory dysfunction could be considered a core feature of ASD and thus used to inform more targeted screening, evaluation, treatment, and research efforts. LAY SUMMARY: The diverse nature of autism spectrum disorder (ASD) makes it difficult to find risk factors and treatment options. We identified the most dissimilar and most similar symptom(s) in children classified as ASD and as having subthreshold ASD characteristics. Factors associated with dysregulation and developmental abilities contributed to diversity in both groups of children. Sensory dysfunction was the most common symptom in children with ASD but not those with subthreshold characteristics. Findings can inform clinical practice and research.

Peri-Pregnancy Cannabis Use and Autism Spectrum Disorder in the Offspring: Findings from the Study to Explore Early Development.

The association of autism spectrum disorder (ASD) with self-reported maternal cannabis use from 3 months pre-conception to delivery ("peri-pregnancy") was assessed in children aged 30-68 months, born 2003 to 2011. Children with ASD (N = 1428) were compared to children with other developmental delays/disorders (DD, N = 1198) and population controls (POP, N = 1628). Peri-pregnancy cannabis use was reported for 5.2% of ASD, 3.2% of DD and 4.4% of POP children. Adjusted odds of peri-pregnancy cannabis use did not differ significantly between ASD cases and DD or POP controls. Results were similar for any use during pregnancy. However, given potential risks suggested by underlying neurobiology and animal models, further studies in more recent cohorts, in which cannabis use and perception may have changed, are needed.

The Impact of Racial and Ethnic Health Disparities in Diabetes Management on Clinical Outcomes: A Reinforcement Learning Analysis of Health Inequity Among Youth and Young Adults in the SEARCH for Diabetes in Youth Study.

OBJECTIVE: To estimate difference in population-level glycemic control and the emergence of diabetes complications given a theoretical scenario in which non-White youth and young adults (YYA) with type 1 diabetes (T1D) receive and follow an equivalent distribution of diabetes treatment regimens as non-Hispanic White YYA. RESEARCH DESIGN AND METHODS: Longitudinal data from YYA diagnosed 2002-2005 in the SEARCH for Diabetes in Youth Study were analyzed. Based on self-reported race/ethnicity, YYA were classified as non-White race or Hispanic ethnicity (non-White subgroup) versus non-Hispanic White race (White subgroup). In the White versus non-White subgroups, the propensity score models estimated treatment regimens, including patterns of insulin modality, self-monitored glucose frequency, and continuous glucose monitoring use. An analysis based on policy evaluation techniques in reinforcement learning estimated the effect of each treatment regimen on mean hemoglobin A1c (HbA1c) and the prevalence of diabetes complications for non-White YYA. RESULTS: The study included 978 YYA. The sample was 47.5% female and 77.5% non-Hispanic White, with a mean age of 12.8 ± 2.4 years at diagnosis. The estimated population mean of longitudinal average HbA1c over visits was 9.2% and 8.2% for the non-White and White subgroup, respectively (difference of 0.9%). Within the non-White subgroup, mean HbA1c across visits was estimated to decrease by 0.33% (95% CI -0.45, -0.21) if these YYA received the distribution of diabetes treatment regimens of the White subgroup, explaining ∼35% of the estimated difference between the two subgroups. The non-White subgroup was also estimated to have a lower risk of developing diabetic retinopathy, diabetic kidney disease, and peripheral neuropathy with the White youth treatment regimen distribution (P < 0.05), although the low proportion of YYA who developed complications limited statistical power for risk estimations. CONCLUSIONS: Mathematically modeling an equalized distribution of T1D self-management tools and technology accounted for part of but not all disparities in glycemic control between non-White and White YYA, underscoring the complexity of race and ethnicity-based health inequity.

Individuals aged 1-64 years with documented congenital heart defects at healthcare encounters, five U.S. surveillance sites, 2011-2013.

BACKGROUND: Many individuals born with congenital heart defects (CHD) survive to adulthood. However, population estimates of CHD beyond early childhood are limited in the U.S. OBJECTIVES: To estimate the percentage of individuals aged 1-to-64 years at five U.S. sites with CHD documented at a healthcare encounter during a three-year period and describe their characteristics. METHODS: Sites conducted population-based surveillance of CHD among 1 to 10-year-olds (three sites) and 11 to 64-year-olds (all five sites) by linking healthcare data. Eligible cases resided in the population catchment areas and had one or more healthcare encounters during the surveillance period (January 1, 2011-December 31, 2013) with a CHD-related ICD-9-CM code. Site-specific population census estimates from the same age groups and time period were used to assess percentage of individuals in the catchment area with a CHD-related ICD-9-CM code documented at a healthcare encounter (hereafter referred to as CHD cases). Severe and non-severe CHD were based on an established mutually exclusive anatomic hierarchy. RESULTS: Among 42,646 CHD cases, 23.7% had severe CHD and 51.5% were male. Percentage of CHD cases among 1 to 10-year-olds, was 6.36/1,000 (range: 4.33-9.96/1,000) but varied by CHD severity [severe: 1.56/1,000 (range: 1.04-2.64/1,000); non-severe: 4.80/1,000 (range: 3.28-7.32/1,000)]. Percentage of cases across all sites in 11 to 64-year-olds was 1.47/1,000 (range: 1.02-2.18/1,000) and varied by CHD severity [severe: 0.34/1,000 (range: 0.26-0.49/1,000); non-severe: 1.13/1,000 (range: 0.76-1.69/1,000)]. Percentage of CHD cases decreased with age until 20 to 44 years and, for non-severe CHD only, increased slightly for ages 45 to 64 years. CONCLUSION: CHD cases varied by site, CHD severity, and age. These findings will inform planning for the needs of this growing population.

The relationship between traffic-related air pollution exposures and allostatic load score among youth with type 1 diabetes in the SEARCH cohort.

OBJECTIVE: We investigated the effects of chronic exposures to particulate and traffic-related air pollution on allostatic load (AL) score, a marker of cumulative biological risk, among youth with type 1 diabetes. RESEARCH DESIGN AND METHODS: Participants were drawn from five clinical sites of the SEARCH for Diabetes in Youth (SEARCH) study (n = 2338). Baseline questionnaires, anthropometric measures, and a fasting blood test were taken at a clinic visit between 2001 and 2005. AL was operationalized using 10 biomarkers reflecting cardiovascular, metabolic, and inflammatory risk. Annual residential exposures to PM2.5 and proximity to heavily-trafficked major roadways were estimated for each participant. Poisson regression models adjusted for sociodemographic and lifestyle factors were conducted for each exposure. RESULTS: No significant associations were observed between exposures to PM2.5 or proximity to traffic and AL score, however analyses were suggestive of effect modification by race for residential distance to heavily-trafficked major roadways (p = 0.02). In stratified analyses, residing <100, 100-<200 and 200-<400 m compared to 400 m or more from heavily-trafficked major roadways was associated with 11%, 26% and 14% increases in AL score, respectively (95% CIs: -4, 29; 9, 45; -1, 30) for non-white participants compared to 6%, -2%, and -2% changes (95% CIs: -2, 15; -10, 7; -8, 6) for white participants. CONCLUSIONS: Among this population of youth with type 1 diabetes, we did not observe consistent relationships between chronic exposures to particulate and traffic-related air pollution and changes in AL score, however associations for traffic-related pollution exposures may differ by race/ethnicity and warrant further examination.

Collection and Storage of Human Plasma for Measurement of Oxylipins.

Oxylipins derived from omega-3 and -6 fatty acids are actively involved in inflammatory and immune processes and play important roles in human disease. However, as the interest in oxylipins increases, questions remain regarding which molecules are detectable in plasma, the best methods of collecting samples, and if molecules are stable during collection and storage. We thereby built upon existing studies by examining the stability of an expanded panel of 90 oxylipins, including specialized pro-resolving lipid mediators (SPMs), in human plasma (n = 5 subjects) during sample collection, processing, and storage at -80 °C. Oxylipins were quantified using liquid chromatography-tandem mass spectrometry (LC/MS/MS). Blood samples collected in ethylenediaminetetraacetic acid (EDTA) or heparin followed by up to 2 h at room temperature prior to processing showed no significant differences in oxylipin concentrations compared to immediately processed samples, including the SPMs lipoxin A4 and resolvin D1. The majority of molecules, including SPMs, remained stable following storage for up to 1 year. However, in support of previous findings, changes were seen in a small subset of oxylipins including 12-HETE, TXB2, 14-HDHA, and 18-HEPE. Overall, this study showed that accurate measurements of most oxylipins can be obtained from stored EDTA or heparin plasma samples using LC/MS/MS.

Association of Lipid Mediators With Development of Future Incident Inflammatory Arthritis in an Anti-Citrullinated Protein Antibody-Positive Population.

OBJECTIVE: To determine the association of polyunsaturated fatty acid (PUFA)-derived lipid mediators with progression from rheumatoid arthritis (RA)-related autoimmunity to inflammatory arthritis (IA). METHODS: We conducted a prospective cohort study using data from the Studies of the Etiology of Rheumatoid Arthritis (SERA). SERA enrolled first-degree relatives (FDRs) of individuals with RA (FDR cohort) and individuals who screened positive for RA-related autoantibodies at health fairs (screened cohort). We followed up 133 anti-cyclic citrullinated peptide 3.1 (anti-CCP3.1)-positive participants, 29 of whom developed IA. Lipid mediators selected a priori were quantified from stored plasma samples using liquid chromatography tandem mass spectrometry. We fit multivariable Cox proportional hazards models for each lipid mediator as a time-varying variable. For lipid mediators found to be significantly associated with IA, we then examined interleukin-1ß (IL-1ß), IL-6, IL-8, and tumor necrosis factor (TNF) as potential statistical mediators. RESULTS: For every 1 natural log pg/ml increase in the circulating plasma levels of proinflammatory 5-HETE, the risk of developing IA increased by 241% (hazard ratio 2.41 [95% confidence interval 1.43-4.07]) after adjusting for age at baseline, cohort (FDR or screened), and shared epitope status. The models examining 15-HETE and 17-HDHA had the same trend but did not reach significance. We did not find evidence that the association between 5-HETE and IA risk was influenced by the proinflammatory cytokines tested. CONCLUSION: In a prospective cohort of anti-CCP-positive individuals, higher levels of 5-HETE, an important precursor to proinflammatory leukotrienes, is associated with subsequent IA. Our findings highlight the potential significance of these PUFA metabolites in pre-RA populations.

Associations Between Socioeconomic Context and Congenital Heart Disease Related Outcomes in Adolescents and Adults.

Little is known about the relation between socioeconomic factors and health outcomes in adults and adolescents with congenital heart defects (CHD). Population-level data from the Colorado CHD surveillance system from 2011 to 2013 was used to examine the association between area deprivation and outcomes including hospitalizations, emergency department visits, cardiac procedures, all-cause and cardiac-related mortality, and major adverse cardiac events. Socioeconomic context was measured by the Area Deprivation Index at census tract level. Missing race/ethnicity was imputed using the Bayesian Improved Surname Geocoding algorithm. Generalized linear models were utilized to examine health disparities across deprivation quintiles after adjusting for insurance type, race/ethnicity, age, gender, urbanicity, and CHD severity in 5,748 patients. Cases residing in the most deprived quintile had 51% higher odds of inpatient admission, 74% higher odds of emergency department visit, 41% higher odds of cardiac surgeries, and 45% higher odds of major adverse cardiac events compared with cases in the least deprived quintile. Further, rates of hospitalizations, emergency department admissions, and cardiac surgeries were elevated in the most deprived compared with the least deprived quintile. Mortality was not significantly different across quintiles. In conclusion, findings suggest significant health equity issues for adolescent and adults with CHD based on area-based deprivation.

The accuracy of provider diagnosed diabetes type in youth compared to an etiologic criteria in the SEARCH for Diabetes in Youth Study.

BACKGROUND: Although surveillance for diabetes in youth relies on provider-assigned diabetes type from medical records, its accuracy compared to an etiologic definition is unknown. METHODS: Using the SEARCH for Diabetes in Youth Registry, we evaluated the validity and accuracy of provider-assigned diabetes type abstracted from medical records against etiologic criteria that included the presence of diabetes autoantibodies (DAA) and insulin sensitivity. Youth who were incident for diabetes in 2002-2006, 2008, or 2012 and had complete data on key analysis variables were included (n = 4001, 85% provider diagnosed type 1). The etiologic definition for type 1 diabetes was ≥1 positive DAA titer(s) or negative DAA titers in the presence of insulin sensitivity and for type 2 diabetes was negative DAA titers in the presence of insulin resistance. RESULTS: Provider diagnosed diabetes type correctly agreed with the etiologic definition of type for 89.9% of cases. Provider diagnosed type 1 diabetes was 96.9% sensitive, 82.8% specific, had a positive predictive value (PPV) of 97.0% and a negative predictive value (NPV) of 82.7%. Provider diagnosed type 2 diabetes was 82.8% sensitive, 96.9% specific, had a PPV and NPV of 82.7% and 97.0%, respectively. CONCLUSION: Provider diagnosis of diabetes type agreed with etiologic criteria for 90% of the cases. While the sensitivity and PPV were high for youth with type 1 diabetes, the lower sensitivity and PPV for type 2 diabetes highlights the value of DAA testing and assessment of insulin sensitivity status to ensure estimates are not biased by misclassification.