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.

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.

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.

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.

Association between diet quality indices and arterial stiffness in youth with type 1 diabetes: SEARCH for Diabetes in Youth Nutrition Ancillary Study.

AIMS: We studied the association of three distinct diet quality indices and two measures of arterial stiffness in youth and young adults (YYA) aged 10 to 30 with T1D. METHODS: Cross-sectional (n = 1421) and longitudinal (n = 520) analyses were conducted in T1D YYA participating in the SEARCH for Diabetes in Youth Study. The diet quality indices included the Dietary Approaches to Stop Hypertension (DASH) index, the Healthy Eating Index 2015 (HEI-2015), and a modified Mediterranean Diet Quality Index (mKIDMED). Arterial stiffness was measured with pulse wave velocity (PWV) and augmentation index (AIx) obtained using a SphygmoCor-Vx device and tonometer. RESULTS: Average diet quality was moderate to poor, with mean scores of 41 (DASH, range 0-80), 55 (HEI-2015, range 0-100), 3.7 (mKIDMED, range - 3-12). None of the diet quality scores was associated with the central PWV or Aix, independent of demographic, clinical and lifestyle factors, body mass index and HbA1c. Longitudinal data yielded consistent findings with cross-sectional results. CONCLUSIONS: This study suggests that diet quality may not function as an independent risk factor for arterial stiffening in YYA with T1D. These findings do not diminish the importance of consuming a quality diet for the management of diabetes, as demonstrated in previous work.

Population-level surveillance of congenital heart defects among adolescents and adults in Colorado: Implications of record linkage.

BACKGROUND: The objective was to describe the design of a population-level electronic health record (EHR) and insurance claims-based surveillance system of adolescents and adults with congenital heart defects (CHDs) in Colorado and to evaluate the bias introduced by duplicate cases across data sources. METHODS: The Colorado CHD Surveillance System ascertained individuals aged 11-64 years with a CHD based on International Classification of Diseases, Ninth Revision, Clinical Modification diagnostic coding between 2011 and 2013 from a diverse network of health care systems and an All Payer Claims Database (APCD). A probability-based identity reconciliation algorithm identified duplicate cases. Logistic regression was conducted to investigate bias introduced by duplicate cases on the relationship between CHD severity (severe compared to moderate/mild) and adverse outcomes including all-cause mortality, inpatient hospitalization, and major adverse cardiac events (myocardial infarction, congestive heart failure, or cerebrovascular event). Sensitivity analyses were conducted to investigate bias introduced by the sole use or exclusion of APCD data. RESULTS: A total of 12,293 unique cases were identified, of which 3,476 had a within or between data source duplicate. Duplicate cases were more likely to be in the youngest age group and have private health insurance, a severe heart defect, a CHD comorbidity, and higher health care utilization. We found that failure to resolve duplicate cases between data sources would inflate the relationship between CHD severity and both morbidity and mortality outcomes by ~15%. Sensitivity analyses indicate that scenarios in which APCD was excluded from case finding or relied upon as the sole source of case finding would also result in an overestimation of the relationship between a CHD severity and major adverse outcomes. DISCUSSION: Aggregated EHR- and claims-based surveillance systems of adolescents and adults with CHD that fail to account for duplicate records will introduce considerable bias into research findings. CONCLUSION: Population-level surveillance systems for rare chronic conditions, such as congenital heart disease, based on aggregation of EHR and claims data require sophisticated identity reconciliation methods to prevent bias introduced by duplicate cases.

A comparison of recreational skiing- and snowboarding-related injuries at a Colorado ski resort, 2012/13-2016/17.

The purpose of this study was to compare injury patterns between recreational skiers and snowboarders. Injured skiers (n = 3,961) and snowboarders (n = 2,428) presented to a mountainside medical clinic, 2012/13-2016/17. Variables investigated for analysis included demographics/characteristics, injury event information, and injury information. Skiers were older than snowboarders (34.3 ± 19.3 vs. 23.2 ± 10.5 years, p < 0.001); a greater proportion of skiers were female (46.3% vs. 27.8%, p < 0.001). Most skiers (84.4%) and snowboarders (84.5%) were helmeted at the time of injury (p = 0.93). Snowboarders were most frequently beginners (38.9%), skiers were intermediates (37.8%). Falls to snow (skiers = 72.3%, snowboarders = 84.8%) and collisions with natural objects (skiers = 9.7%, snowboarders = 7.4%) were common injury mechanisms. Common skiing injuries were knee sprains (20.5%) and head trauma (8.9%); common snowboarding injuries were wrist fractures (25.7%), shoulder separations (9.1%), and head trauma (9.0%). Given that injury patterns significantly differ between sports, it is important for clinicians, ski patrollers, and resorts to develop and deliver sport-specific injury prevention interventions to most effectively decrease injury burden.

A hybrid approach to record linkage using a combination of deterministic and probabilistic methodology.

OBJECTIVE: The disjointed healthcare system and the nonexistence of a universal patient identifier across systems necessitates accurate record linkage (RL). We aim to describe the implementation and evaluation of a hybrid record linkage method in a statewide surveillance system for congenital heart disease. MATERIALS AND METHODS: Clear-text personally identifiable information on individuals in the Colorado Congenital Heart Disease surveillance system was obtained from 5 electronic health record and medical claims data sources. Two deterministic methods and 1 probabilistic RL method using first name, last name, social security number, date of birth, and house number were initially implemented independently and then sequentially in a hybrid approach to assess RL performance. RESULTS: 16 480 nonunique individuals with congenital heart disease were ascertained. Deterministic linkage methods, when performed independently, yielded 4505 linked pairs (consisting of 2 records linked together within or across data sources). Probabilistic RL, using 3 initial characters of last name and gender for blocking, yielded 6294 linked pairs when executed independently. Using a hybrid linkage routine resulted in 6451 linkages and an additional 18%-24% correct linked pairs as compared to the independent methods. A hybrid linkage routine resulted in higher recall and F-measure scores compared to probabilistic and deterministic methods performed independently. DISCUSSION: The hybrid approach resulted in increased linkage accuracy and identified pairs of linked record that would have otherwise been missed when using any independent linkage technique. CONCLUSION: When performing RL within and across disparate data sources, the hybrid RL routine outperformed independent deterministic and probabilistic methods.

Estimating the prevalence of congenital heart disease among adolescents and adults in Colorado adjusted for incomplete case ascertainment.

BACKGROUND: Congenital heart defects (CHDs), the most common type of birth defect in the United States, are increasing in prevalence in the general population. Though CHD prevalence at birth has been well described in the United States at about 1%, little is known about long-term survival and prevalence of CHDs beyond childhood. This study aimed to estimate the prevalence of CHDs among adolescents and adults in Colorado. METHODS: The prevalence of CHDs among adolescents and adults residing in Colorado during 2011 to 2013 was estimated using log-linear capture-recapture methods to account for incomplete case ascertainment. Five case-finding data sources were used for this analysis including electronic health record data from 4 major health systems and a state-legislated all payer claims database. RESULTS: Twelve thousand two hundred ninety-three unique individuals with CHDs (2481 adolescents and 9812 adults) were identified in one or more primary data sources. We estimated the crude prevalence of CHDs in adolescents and adults in Colorado to be 3.22 per 1000 individuals (95% CI 3.19-3.53). After accounting for incomplete case ascertainment, the final capture-recapture model yielded an estimated total adolescent and adult CHD population of 23,194 (95% CI 22,419-23,565) and an adjusted prevalence of 6.07 per 1000 individuals (95% CI 5.86-6.16), indicating 47% of the cases in the catchment area were not identified in the case-identifying data sources. CONCLUSION: This statewide study yielded new information on the prevalence of CHDs in adolescents and adults. These high prevalence rates underscore the need for additional specialized care facilities for this population with CHDs.

Impact of an incentive-based prenatal smoking cessation program for low-income women in Colorado.

OBJECTIVE: To assess birth outcomes and cost-savings of an incentive-based prenatal smoking cessation program targeting low-income women in Colorado. DESIGN: Prospective observational cohort with nonequivalent population control groups. SAMPLE: Program participants (n = 2,231) linked to the birth certificate to ascertain birth outcomes compared to two reference populations from Pregnancy Risk Assessment Monitoring System (PRAMS) and Colorado live births based on the birth certificate. MEASUREMENTS: Tobacco cessation metrics in the third trimester of pregnancy, neonatal low birth weight (<2,500 g), preterm birth (birth at <37 weeks gestation), neonatal intensive care unit (NICU) admission and maternal gestational hypertension. Cost-savings and return on investment (ROI) were projected using average Medicaid reimbursement. RESULTS: Infants of mothers enrolled in the program had a lower risk of low birthweight (RR = 0.86; 95% CI = 0.75, 0.97), preterm birth (PTB) (RR = 0.76; 95% CI = 0.65, 0.88) and neonatal intensive care unit (NICU) admission (RR = 0.76; 95% CI = 0.66, 0.88) compared to the birth certificate population, corresponding to a ROI of $7.73 and an individual cost savings of $6,040. Compared to PRAMS, infants of enrolled mothers had a lower risk of PTB (RR = 0.72; 95% CI = 0.53, 0.99) and NICU admission (RR = 0.45; 95% CI = 0.32, 0.62), corresponding to an ROI of $2.79 and an individual cost savings of $2,182. CONCLUSIONS: We found a reduction of adverse birth outcomes, and cost savings.

Inflammation and acute traffic-related air pollution exposures among a cohort of youth with type 1 diabetes.

BACKGROUND: Evidence remains equivocal regarding the association of inflammation, a precursor to cardiovascular disease, and acute exposures to ambient air pollution from traffic-related particulate matter. Though youth with type 1 diabetes are at higher risk for cardiovascular disease, the relationship of inflammation and ambient air pollution exposures in this population has received little attention. OBJECTIVES: Using five geographically diverse US sites from the racially- and ethnically-diverse SEARCH for Diabetes in Youth Cohort, we examined the relationship of acute exposures to PM2.5 mass, Atmospheric Dispersion Modeling System (ADMS)-Roads traffic-related PM concentrations near roadways, and elemental carbon (EC) with biomarkers of inflammation including interleukin-6 (IL-6), c-reactive protein (hs-CRP) and fibrinogen. METHODS: Baseline questionnaires and blood were obtained at a study visit. Using a spatio-temporal modeling approach, pollutant exposures for 7 days prior to blood draw were assigned to residential addresses. Linear mixed models for each outcome and exposure were adjusted for demographic and lifestyle factors identified a priori. RESULTS: Among the 2566 participants with complete data, fully-adjusted models showed positive associations of EC average week exposures with IL-6 and hs-CRP, and PM2.5 mass exposures on lag day 3 with IL-6 levels. Comparing the 25th and 75th percentiles of average week EC exposures resulted in 8.3% higher IL-6 (95%CI: 2.7%,14.3%) and 9.8% higher hs-CRP (95%CI: 2.4%,17.7%). We observed some evidence of effect modification for the relationships of PM2.5 mass exposures with hs-CRP by gender and with IL-6 by race/ethnicity. CONCLUSIONS: Indicators of inflammation were associated with estimated traffic-related air pollutant exposures in this study population of youth with type 1 diabetes. Thus youth with type 1 diabetes may be at increased risk of air pollution-related inflammation. These findings and the racial/ethnic and gender differences observed deserve further exploration.

Exposure to Diabetes in Utero Is Associated with Earlier Pubertal Timing and Faster Pubertal Growth in the Offspring: The EPOCH Study.

OBJECTIVE: To examine the associations of in utero exposure to maternal diabetes with surrogate measures of offspring pubertal timing (age at peak height velocity [APHV]) and speed of pubertal growth (peak height velocity [PHV]). STUDY DESIGN: Data from 77 exposed and 340 unexposed youth followed from age 2 to 19 years (51% non-Hispanic white, 50% female) were analyzed using the Exploring Perinatal Outcomes among Children study, a historical prospective cohort. Maternal diabetes status was collected from obstetric records, and child heights from 2 years to current age from pediatric records. Other covariates were collected during research visits. The superimposition by translation and rotation method, using height measurements (4-52 per participant), modeled APHV and PHV. Accelerated failure time analyses were used to test whether exposure to maternal diabetes was associated with younger APHV and faster PHV. RESULTS: Adjusting for child's sex, race/ethnicity, and socioeconomic status, median APHV was reached ~3 months earlier in youth exposed to maternal diabetes compared with unexposed youth (P < .03). Youth exposed to maternal diabetes had a faster PHV than unexposed youth: exposed girls had 10.5% greater median PHV compared with unexposed girls and exposed boys had a 4.0% greater median PHV compared with unexposed boys (P < .001 for exposure by sex interaction). CONCLUSIONS: Our findings provide evidence that exposure to maternal diabetes in utero is associated with earlier pubertal timing and faster pubertal growth. Whether earlier puberty or faster speed of pubertal growth mediates the association between maternal diabetes exposure and later chronic disease risk remains to be studied.

Cannabis Use During the Perinatal Period in a State With Legalized Recreational and Medical Marijuana: The Association Between Maternal Characteristics, Breastfeeding Patterns, and Neonatal Outcomes.

OBJECTIVES: To evaluate state-level prevalence estimates of prenatal and early postnatal cannabis use in a state with legalized medical and recreational marijuana and the association with adverse neonatal outcomes. STUDY DESIGN: We conducted a cross-sectional study on 3,207 respondents from the 2014-2015 Colorado Pregnancy Risk Assessment Monitoring System with state-developed questions on cannabis use. Differences in perinatal cannabis use were evaluated according to maternal characteristics, breastfeeding patterns, and pregnancy intendedness. Multiple logistic regression models evaluated the relationship between prenatal cannabis use and adverse neonatal outcomes including low birth weight, small for gestational age, preterm birth, and admission to the neonatal intensive care unit. RESULTS: The self-reported prevalence of cannabis use at any time during pregnancy was 5.7 ± 0.5% and the prevalence of early postnatal cannabis use among women who breastfed was 5.0% (95% CI, 4.1%-6.2%). Prenatal cannabis use was associated with a 50% increased likelihood of low birth weight, independent of maternal age, race/ethnicity, level of education, and tobacco use during pregnancy (OR, 1.5; 95% CI, 1.1-2.1; P = .02). Small for gestational age, preterm birth, and neonatal intensive care unit admission were not associated with prenatal cannabis use, independent of prenatal tobacco use. CONCLUSIONS: Our findings underscore the importance of screening for cannabis use during prenatal care and the need for provider counselling about the adverse health consequences of continued use during pregnancy and lactation.

Factors influencing time to case registration for youth with type 1 and type 2 diabetes: SEARCH for Diabetes in Youth Study.

PURPOSE: The development of a sustainable pediatric diabetes surveillance system for the United States requires a better understanding of issues related to case ascertainment. METHODS: Using the SEARCH for Diabetes in Youth registry, we examined whether time from diabetes diagnosis to case registration differed by diabetes type, patient demographics, and the type of provider reporting the case to the study. Plots for time from diagnosis to registration were developed, and differences by key variables were examined using the log-rank test. RESULTS: Compared with time to registration for type 1 cases, it took 2.6 (95% confidence interval [CI], 2.5-2.6) times longer to register 50% of type 2 diabetes cases, and 2.3 (95% CI, 2.0-2.5) times longer to register 90% of type 2 cases. For type 1 diabetes cases, a longer time to registration was associated with older age, minority race/ethnicity, and cases, where the referring provider was not an endocrinologist. For type 2 diabetes cases, older age, non-Hispanic white race/ethnicity, and cases reported by providers other than an endocrinologist took longer to identify and register. CONCLUSIONS: These findings highlight the need for continued childhood diabetes surveillance to identify future trends and influences on changes in prevalence and incidence.

Maternal dietary intake during pregnancy and offspring body composition: The Healthy Start Study.

BACKGROUND: Consistent evidence of an influence of maternal dietary intake during pregnancy on infant body size and composition in human populations is lacking, despite robust evidence in animal models. OBJECTIVE: We sought to evaluate the influence of maternal macronutrient intake and balance during pregnancy on neonatal body size and composition, including fat mass and fat-free mass. STUDY DESIGN: The analysis was conducted among 1040 mother-offspring pairs enrolled in the prospective prebirth observational cohort: the Healthy Start Study. Diet during pregnancy was collected using repeated 24-hour dietary recalls (up to 8). Direct measures of body composition were obtained using air displacement plethysmography. The National Cancer Institute measurement error model was used to estimate usual dietary intake during pregnancy. Multivariable partition (nonisocaloric) and nutrient density (isocaloric) linear regression models were used to test the associations between maternal dietary intake and neonatal body composition. RESULTS: The median macronutrient composition during pregnancy was 32.2% from fat, 15.0% from protein, and 47.8% from carbohydrates. In the partition multivariate regression model, individual macronutrient intake values were not associated with birthweight or fat-free mass, but were associated with fat mass. Respectively, 418 kJ increases in total fat, saturated fat, unsaturated fat, and total carbohydrates were associated with 4.2-g (P = .03), 11.1-g (P = .003), 5.9-g (P = .04), and 2.9-g (P = .02) increases in neonatal fat mass, independent of prepregnancy body mass index. In the nutrient density multivariate regression model, macronutrient balance was not associated with fat mass, fat-free mass, or birthweight after adjustment for prepregnancy body mass index. CONCLUSION: Neonatal adiposity, but not birthweight, is independently associated with increased maternal intake of total fat, saturated fat, unsaturated fat, and total carbohydrates, but not protein, suggesting that most forms of increased caloric intake contribute to fetal fat accretion.

Sugar-sweetened beverage intake and cardiovascular risk factor profile in youth with type 1 diabetes: application of measurement error methodology in the SEARCH Nutrition Ancillary Study.

The SEARCH Nutrition Ancillary Study aims to investigate the role of dietary intake on the development of long-term complications of type 1 diabetes in youth, and capitalise on measurement error (ME) adjustment methodology. Using the National Cancer Institute (NCI) method for episodically consumed foods, we evaluated the relationship between sugar-sweetened beverage (SSB) intake and cardiovascular risk factor profile, with the application of ME adjustment methodology. The calibration sample included 166 youth with two FFQ and three 24 h dietary recall data within 1 month. The full sample included 2286 youth with type 1 diabetes. SSB intake was significantly associated with higher TAG, total and LDL-cholesterol concentrations, after adjusting for energy, age, diabetes duration, race/ethnicity, sex and education. The estimated effect size was larger (model coefficients increased approximately 3-fold) after the application of the NCI method than without adjustment for ME. Compared with individuals consuming one serving of SSB every 2 weeks, those who consumed one serving of SSB every 2 d had 3.7 mg/dl (0.04 mmol/l) higher TAG concentrations and 4.0 mg/dl (0.10 mmol/l) higher total cholesterol and LDL-cholesterol concentrations, after adjusting for ME and covariates. SSB intake was not associated with measures of adiposity and blood pressure. Our findings suggest that SSB intake is significantly related to increased lipid levels in youth with type 1 diabetes, and that estimates of the effect size of SSB on lipid levels are severely attenuated in the presence of ME. Future studies in youth with diabetes should consider a design that will allow for the adjustment for ME when studying the influence of diet on health status.

Assessing age-related etiologic heterogeneity in the onset of islet autoimmunity.

Type 1 diabetes (T1D), a chronic autoimmune disease, is often preceded by a preclinical phase of islet autoimmunity (IA) where the insulin-producing beta cells of the pancreas are destroyed and circulating autoantibodies can be detected. The goal of this study was to demonstrate methods for identifying exposures that differentially influence the disease process at certain ages by assessing age-related heterogeneity. The Diabetes Autoimmunity Study in the Young (DAISY) has followed 2,547 children at increased genetic risk for T1D from birth since 1993 in Denver, Colorado, 188 of whom developed IA. Using the DAISY population, we evaluated putative determinants of IA, including non-Hispanic white (NHW) ethnicity, maternal age at birth, and erythrocyte membrane n-3 fatty acid (FA) levels, for age-related heterogeneity. A supremum test, weighted Schoenfeld residuals, and restricted cubic splines were used to assess nonproportional hazards, that is, an age-related association of the exposure with IA risk. NHW ethnicity, maternal age, and erythrocyte membrane n-3 FA levels demonstrated a significant age-related association with IA risk. Assessing heterogeneity in disease etiology enables researchers to identify associations that may lead to better understanding of complex chronic diseases.