Effects of a community gardening intervention on diet, physical activity, and anthropometry outcomes in the USA (CAPS): an observer-blind, randomised controlled trial.

BACKGROUND: Unhealthy diet, physical inactivity, and social disconnection are important modifiable risk factors for non-communicable and other chronic diseases, which might be alleviated through nature-based community interventions. We tested whether a community gardening intervention could reduce these common health risks in an adult population that is diverse in terms of age, ethnicity, and socioeconomic status. METHODS: In this observer-blind, randomised, controlled trial, we recruited individuals who were on Denver Urban Garden waiting lists for community gardens in Denver and Aurora (CO, USA), aged 18 years or older, and had not gardened in the past 2 years. Participants were randomly assigned (1:1), using a randomised block design in block sizes of two, four, or six, to receive a community garden plot (intervention group) or remain on a waiting list and not garden (control group). Researchers were masked to group allocation. Primary outcomes were diet, physical activity, and anthropometry; secondary outcomes were perceived stress and anxiety. During spring (April to early June, before randomisation; timepoint 1 [T1]), autumn (late August to October; timepoint 2 [T2]), and winter (January to March, after the intervention; timepoint 3 [T3]), participants completed three diet recalls, 7-day accelerometry, surveys, and anthropometry. Analyses were done using the intention-to-treat principle (ie, including all participants randomly assigned to groups, and assessed as randomised). We used mixed models to test time-by-intervention hypotheses at an α level of 0·04, with T2 and T3 intervention effects at an α level of 0·005 (99·5% CI). Due to potential effects of the COVID-19 pandemic on outcomes, we excluded all participant data collected after Feb 1, 2020. This study is registered with ClinicalTrials.gov, NCT03089177, and data collection is now complete. FINDINGS: Between Jan 1, 2017, and June 15, 2019, 493 adults were screened and 291 completed baseline measures and were randomly assigned to the intervention (n=145) or control (n=146) groups. Mean age was 41·5 years (SD 13·5), 238 (82%) of 291 participants were female, 52 (18%) were male, 99 (34%) identified as Hispanic, and 191 (66%) identified as non-Hispanic. 237 (81%) completed measurements before the beginning of the COVID-19 pandemic. One (<1%) participant in the intervention group had an adverse allergic event in the garden. Significant time-by-intervention effects were observed for fibre intake (p=0·034), with mean between-group difference (intervention minus control) at T2 of 1·41 g per day (99·5% CI -2·09 to 4·92), and for moderate-to-vigorous physical activity (p=0·012), with mean between-group difference of 5·80 min per day (99·5% CI -4·44 to 16·05). We found no significant time-by-intervention interactions for combined fruit and vegetable intake, Healthy Eating Index (measured using Healthy Eating Index-2010), sedentary time, BMI, and waist circumference (all p>0·04). Difference score models showed greater reductions between T1 and T2 in perceived stress and anxiety among participants in the intervention group than among those in the control group. INTERPRETATION: Community gardening can provide a nature-based solution, accessible to a diverse population including new gardeners, to improve wellbeing and important behavioural risk factors for non-communicable and chronic diseases. FUNDING: American Cancer Society, University of Colorado Cancer Centre, University of Colorado Boulder, National Institutes of Health, US Department of Agriculture National Institute of Food and Agriculture, Michigan AgBioResearch Hatch projects.

Determining diagnosis date of diabetes using structured electronic health record (EHR) data: the SEARCH for diabetes in youth study.

BACKGROUND: Disease surveillance of diabetes among youth has relied mainly upon manual chart review. However, increasingly available structured electronic health record (EHR) data have been shown to yield accurate determinations of diabetes status and type. Validated algorithms to determine date of diabetes diagnosis are lacking. The objective of this work is to validate two EHR-based algorithms to determine date of diagnosis of diabetes. METHODS: A rule-based ICD-10 algorithm identified youth with diabetes from structured EHR data over the period of 2009 through 2017 within three children's hospitals that participate in the SEARCH for Diabetes in Youth Study: Cincinnati Children's Hospital, Cincinnati, OH, Seattle Children's Hospital, Seattle, WA, and Children's Hospital Colorado, Denver, CO. Previous research and a multidisciplinary team informed the creation of two algorithms based upon structured EHR data to determine date of diagnosis among diabetes cases. An ICD-code algorithm was defined by the year of occurrence of a second ICD-9 or ICD-10 diabetes code. A multiple-criteria algorithm consisted of the year of first occurrence of any of the following: diabetes-related ICD code, elevated glucose, elevated HbA1c, or diabetes medication. We assessed algorithm performance by percent agreement with a gold standard date of diagnosis determined by chart review. RESULTS: Among 3777 cases, both algorithms demonstrated high agreement with true diagnosis year and differed in classification (p = 0.006): 86.5% agreement for the ICD code algorithm and 85.9% agreement for the multiple-criteria algorithm. Agreement was high for both type 1 and type 2 cases for the ICD code algorithm. Performance improved over time. CONCLUSIONS: Year of occurrence of the second ICD diabetes-related code in the EHR yields an accurate diagnosis date within these pediatric hospital systems. This may lead to increased efficiency and sustainability of surveillance methods for incidence of diabetes among youth.

Trends in Prevalence of Type 1 and Type 2 Diabetes in Children and Adolescents in the US, 2001-2017.

Importance: Changes in the prevalence of youth-onset diabetes have previously been observed. Objective: To estimate changes in prevalence of type 1 and type 2 diabetes in youths in the US from 2001 to 2017. Design, Setting, and Participants: In this cross-sectional observational study, individuals younger than 20 years with physician-diagnosed diabetes were enumerated from 6 areas in the US (4 geographic areas, 1 health plan, and select American Indian reservations) for 2001, 2009, and 2017. Exposures: Calendar year. Main Outcomes and Measures: Estimated prevalence of physician-diagnosed type 1 and type 2 diabetes overall and by race and ethnicity, age, and sex. Results: Among youths 19 years or younger, 4958 of 3.35 million had type 1 diabetes in 2001, 6672 of 3.46 million had type 1 diabetes in 2009, and 7759 of 3.61 million had type 1 diabetes in 2017; among those aged 10 to 19 years, 588 of 1.73 million had type 2 diabetes in 2001, 814 of 1.85 million had type 2 diabetes in 2009, and 1230 of 1.85 million had type 2 diabetes in 2017. The estimated type 1 diabetes prevalence per 1000 youths for those 19 years or younger increased significantly from 1.48 (95% CI, 1.44-1.52) in 2001 to 1.93 (95% CI, 1.88-1.98) in 2009 to 2.15 (95% CI, 2.10-2.20) in 2017, an absolute increase of 0.67 per 1000 youths (95%, CI, 0.64-0.70) and a 45.1% (95% CI, 40.0%-50.4%) relative increase over 16 years. The greatest absolute increases were observed among non-Hispanic White (0.93 per 1000 youths [95% CI, 0.88-0.98]) and non-Hispanic Black (0.89 per 1000 youths [95% CI, 0.88-0.98]) youths. The estimated type 2 diabetes prevalence per 1000 youths aged 10 to 19 years increased significantly from 0.34 (95% CI, 0.31-0.37) in 2001 to 0.46 (95% CI, 0.43-0.49) in 2009 to 0.67 (95% CI, 0.63-0.70) in 2017, an absolute increase of 0.32 per 1000 youths (95% CI, 0.30-0.35) and a 95.3% (95% CI, 77.0%-115.4%) relative increase over 16 years. The greatest absolute increases were observed among non-Hispanic Black (0.85 per 1000 youths [95% CI, 0.74-0.97]) and Hispanic (0.57 per 1000 youths [95% CI, 0.51-0.64]) youths. Conclusions and Relevance: In 6 areas of the US from 2001 to 2017, the estimated prevalence of diabetes among children and adolescents increased for both type 1 and type 2 diabetes.

Twenty years of pediatric diabetes surveillance: what do we know and why it matters.

SEARCH for Diabetes in Youth (SEARCH) was initiated in 2000 as a multicenter study to address major gaps in the understanding of childhood diabetes in the United States. An active registry of youth diagnosed with diabetes at age <20 years since 2002 assessed prevalence, annual incidence, and trends by age, race/ethnicity, sex, and diabetes type. An observational cohort nested within the population-based registry was established to assess the natural history and risk factors for acute and chronic diabetes-related complications, as well as the quality of care and quality of life of children and adolescents with diabetes from diagnosis into young adulthood. SEARCH findings have contributed to a better understanding of the complex and heterogeneous nature of youth-onset diabetes. Continued surveillance of the burden and risk of type 1 and type 2 diabetes is important to track and monitor incidence and prevalence within the population. SEARCH reported evidence of early diabetes complications highlighting that continuing the long-term follow-up of youth with diabetes is necessary to further our understanding of its natural history and to develop the most appropriate approaches to primary, secondary, and tertiary prevention of diabetes and its complications. This review summarizes two decades of research and suggests avenues for further work.

Urine tungsten and chronic kidney disease in rural Colorado.

BACKGROUND: Chronic kidney disease (CKD) is a cause of global morbidity and mortality in agricultural communities. The San Luis Valley (SLV) is a rural agricultural community in southern Colorado with geographic and sociodemographic risk factors for CKD, including a water supply contaminated by heavy metals. METHODS: We obtained pre-existing sociodemographic, clinical, and urine trace metal data for 1659 subjects from the San Luis Valley Diabetes Study, a prospective cohort study. We assessed prospective associations between urine tungsten (W) and time-to-CKD using accelerated failure time models (n = 1659). Additionally, logistic models were used to assess relationships between urine W and renal injury markers (NGAL, KIM1) using Tobit regression (n = 816), as well as epidemiologically-defined CKD of unknown origin (CKDu) using multiple logistic regression (n = 620). RESULTS: Elevated urine W was strongly associated with decreased time-to-CKD, even after controlling for hypertension and diabetes. Depending on how CKD was defined, a doubling of urine W was associated with a 27% (95% CI 11%, 46%) to 31% (14%, 51%) higher odds of developing CKD within 5 years. The relationship between urine W and select renal injury markers was not significant, although urine NGAL was modified by diabetes status. Elevated (>95%ile) urinary W was significantly associated with CKDu (OR 5.93, 1.83, 19.21) while adjusting for known CKD risk factors. CONCLUSIONS: Our data suggest that increased exposure to W is associated with decreased time-to-CKD and may be associated with CKDu. Given persistence of associations after controlling for diabetes and hypertension, W may exert a primary effect on the kidney, although this needs to be evaluated further in future studies.

Diabetic ketoacidosis at diagnosis among youth with type 1 and type 2 diabetes: Results from SEARCH (United States) and YDR (India) registries.

BACKGROUND: There is significant global variation in the prevalence of diabetic ketoacidosis (DKA) at diagnosis among youth with type 1 diabetes (T1D). However, data for youth with type 2 diabetes (T2D) are limited, even in developed countries. We compared the prevalence of DKA at diagnosis among individuals with T1D and T2D from the SEARCH for Diabetes in Youth (SEARCH) and the Registry of Youth Onset Diabetes in India (YDR) registries. METHODS: We harmonized the SEARCH and YDR registries to the structure and terminology in the Observational Medical Outcome Partnership Common Data Model. Data used were from youth with T1D and T2D diagnosed before 20 years and newly diagnosed between 2006 and 2012 in YDR and 2009 and 2012 in SEARCH. RESULTS: There were 5366 US youth (4078 with T1D, 1288 with T2D) and 2335 Indian youth (2108 with T1D, 227 with T2D). More than one third of T1D youth enrolled in SEARCH had DKA at diagnosis which was significantly higher than in YDR (35.3% vs 28.7%, P < .0001). The burden of DKA in youth with T1D was significantly higher among younger age groups; this relationship was similar across registries (P = .4). The prevalence of DKA among T2D in SEARCH and YDR were 5.5% and 6.6% respectively (P = .4). CONCLUSIONS: There is significant burden of DKA at diagnosis with T1D among youth from United States and India, especially among the younger age groups. The reasons for this high prevalence are largely unknown but are critical to developing interventions to prevent DKA at diagnosis.

Clinical profile at diagnosis with youth-onset type 1 and type 2 diabetes in two pediatric diabetes registries: SEARCH (United States) and YDR (India).

BACKGROUND: Over the last decades, diabetes in youth has increased in both India and the United States, along with the burden of long-term complications and healthcare costs. However, there are limited standardized population-based data in contemporary youth cohorts for comparison of clinical and demographic characteristics of diabetes for both type 1 (T1D) and type 2 (T2D). METHODS: In partnership, we harmonized demographic and clinical data from the SEARCH for Diabetes in Youth (SEARCH) registry in the United States and the Registry of People with Diabetes with Youth Age at Onset (YDR) in India to the structure and terminology of the Observational Medical Outcomes Partnership Common Data Model. Data were from youth with T1D and T2D, aged <20 years and newly diagnosed between 2006 and 2010. We compared key characteristics across registries using χ2 tests and t-tests. RESULTS: In total, there were 9650 youth with T1D and 2406 youth with T2D from 2006 to 2012. SEARCH youth were diagnosed at younger ages than YDR youth for T1D and T2D (10.0 vs 10.5 years, P < .001 and 14.7 vs 16.1 years, P < .001, respectively). For T2D, SEARCH had a higher proportion of females and significantly lower proportion of youth of high socioeconomic status compared to YDR. For T1D and T2D, SEARCH youth had higher BMI, lower blood pressure, and lower A1c compared to YDR youth. CONCLUSIONS: These data offer insights into the demographic and clinical characteristics of diabetes in youth across the two countries. Further research is needed to better understand why these differences exist.

Treatment regimens and glycosylated hemoglobin levels in youth with Type 1 and Type 2 diabetes: Data from SEARCH (United States) and YDR (India) registries.

OBJECTIVE: To compare treatment regimens and glycosylated hemoglobin (A1c) levels in Type 1 (T1D) and Type 2 diabetes (T2D) using diabetes registries from two countries-U.S. SEARCH for Diabetes in Youth (SEARCH) and Indian Registry of youth onset diabetes in India (YDR). METHODS: The SEARCH and YDR data were harmonized to the structure and terminology in the Observational Medical Outcomes Partnership Common Data Model. Data used were from T1D and T2D youth diagnosed <20 years between 2006-2012 for YDR, and 2006, 2008, and 2012 for SEARCH. We compared treatment regimens and A1c levels across the two registries. RESULTS: There were 4003 T1D (SEARCH = 1899; YDR = 2104) and 611 T2D (SEARCH = 384; YDR = 227) youth. The mean A1c was higher in YDR compared to SEARCH (T1D:11.0% ± 2.9% vs 7.8% ± 1.7%, P < .001; T2D:9.9% ± 2.8% vs 7.2% ± 2.1%, P < .001). Among T1D youth in SEARCH, 65.1% were on a basal/bolus regimen, whereas in YDR, 52.8% were on once/twice daily insulin regimen. Pumps were used by 16.2% of SEARCH and 1.5% of YDR youth with T1D. Among T2D youth, in SEARCH and YDR, a majority were on metformin only (43.0% vs 30.0%), followed by insulin + any oral hypoglycemic agents (26.3% vs 13.7%) and insulin only (12.8% vs 18.9%), respectively. CONCLUSION: We found significant differences between SEARCH and YDR in treatment patterns in T1D and T2D. A1c levels were higher in YDR than SEARCH youth, for both T1D and T2D, irrespective of the regimens used. Efforts to achieve better glycemic control for youth are urgently needed to reduce the risk of long-term complications.

Comparison of the incidence of diabetes in United States and Indian youth: An international harmonization of youth diabetes registries.

OBJECTIVE: Incidence of youth-onset diabetes in India has not been well described. Comparison of incidence, across diabetes registries, has the potential to inform hypotheses for risk factors. We sought to compare the incidence of diabetes in the U.S.-based registry of youth onset diabetes (SEARCH) to the Registry of Diabetes with Young Age at Onset (YDR-Chennai and New Delhi regions) in India. METHODS: We harmonized data from both SEARCH and YDR to the Observational Medical Outcomes Partnership (OMOP) Common Data Model. Data were from youth registered with incident diabetes (2006-2012). Denominators were from census and membership data. We calculated diabetes incidence by averaging the total cases across the entire follow-up period and dividing this by the estimated census population corresponding to the source population for case ascertainment. Incidence was calculated for each of the registries and compared by type and within age and sex categories using a 2-sided, skew-corrected inverted score test. RESULTS: Incidence of type 1 was higher in SEARCH (21.2 cases/100 000 [95% CI: 19.9, 22.5]) than YDR (4.9 cases/100 000 [95% CI: 4.3, 5.6]). Incidence of type 2 diabetes was also higher in SEARCH (5.9 cases/100 000 [95% CI: 5.3, 6.6] in SEARCH vs 0.5/cases/100 000 [95% CI: 0.3, 0.7] in YDR). The age distribution of incident type 1 diabetes cases was similar across registries, whereas type 2 diabetes incidence was higher at an earlier age in SEARCH. Sex differences existed in SEARCH only, with a higher rate of type 2 diabetes among females. CONCLUSION: The incidence of youth-onset type 1 and 2 diabetes was significantly different between registries. Additional data are needed to elucidate whether the differences observed represent diagnostic delay, differences in genetic susceptibility, or differences in distribution of risk factors.

Hepatic lipase (LIPC) sequencing in individuals with extremely high and low high-density lipoprotein cholesterol levels.

Common variants in the hepatic lipase (LIPC) gene have been shown to be associated with plasma lipid levels; however, the distribution and functional features of rare and regulatory LIPC variants contributing to the extreme lipid phenotypes are not well known. This study was aimed to catalogue LIPC variants by resequencing the entire LIPC gene in 95 non-Hispanic Whites (NHWs) and 95 African blacks (ABs) with extreme HDL-C levels followed by in silico functional analyses. A total of 412 variants, including 43 novel variants were identified; 56 were unique to NHWs and 234 were unique to ABs. Seventy-eight variants in NHWs and 89 variants in ABs were present either in high HDL-C group or low HDL-C group. Two non-synonymous variants (p.S289F, p.T405M), found in NHWs with high HDL-C group were predicted to have damaging effect on LIPC protein by SIFT, MT2 and PP2. We also found several non-coding variants that possibly reside in the circRNA and lncRNA binding sites and may have regulatory potential, as identified in rSNPbase and RegulomeDB databases. Our results shed light on the regulatory nature of rare and non-coding LIPC variants as well as suggest their important contributions in affecting the extreme HDL-C phenotypes.

Prenatal Exposure to Per- and Polyfluoroalkyl Substances, Umbilical Cord Blood DNA Methylation, and Cardio-Metabolic Indicators in Newborns: The Healthy Start Study.

BACKGROUND: Per- and polyfluoroalkyl substances (PFAS) are environmentally persistent chemicals widely detected in women of reproductive age. Prenatal PFAS exposure is associated with adverse health outcomes in children. We hypothesized that DNA methylation changes may result from prenatal PFAS exposure and may be linked to offspring cardio-metabolic phenotype. OBJECTIVES: We estimated associations of prenatal PFAS with DNA methylation in umbilical cord blood. We evaluated associations of methylation at selected sites with neonatal cardio-metabolic indicators. METHODS: Among 583 mother-infant pairs in a prospective cohort, five PFAS were quantified in maternal serum (median 27 wk of gestation). Umbilical cord blood DNA methylation was evaluated using the Illumina HumanMethylation450 array. Differentially methylated positions (DMPs) were evaluated at a false discovery rate (FDR)<0.05 and differentially methylated regions (DMRs) were identified using comb-p (Sidák-adjusted p<0.05). We estimated associations between methylation at candidate DMPs and DMR sites and the following outcomes: newborn weight, adiposity, and cord blood glucose, insulin, lipids, and leptin. RESULTS: Maternal serum PFAS concentrations were below the median for females in the U.S. general population. Moderate to high pairwise correlations were observed between PFAS concentrations (ρ=0.28-0.76). Methylation at one DMP (cg18587484), annotated to the gene TJAP1, was associated with perfluorooctanoate (PFOA) at FDR< 0.05. Comb-p detected between 4 and 15 DMRs for each PFAS. Associated genes, some common across multiple PFAS, were implicated in growth (RPTOR), lipid homeostasis (PON1, PON3, CIDEB, NR1H2), inflammation and immune activity (RASL11B, RNF39), among other functions. There was suggestive evidence that two PFAS-associated loci (cg09093485, cg09637273) were associated with cord blood triglycerides and birth weight, respectively (FDR< 0.1). DISCUSSION: DNA methylation in umbilical cord blood was associated with maternal serum PFAS concentrations during pregnancy, suggesting potential associations with offspring growth, metabolism, and immune function. Future research should explore whether DNA methylation changes mediate associations between prenatal PFAS exposures and child health outcomes. https://doi.org/10.1289/EHP6888.

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.

Detection of Diabetes Status and Type in Youth Using Electronic Health Records: The SEARCH for Diabetes in Youth Study.

OBJECTIVE: Diabetes surveillance often requires manual medical chart reviews to confirm status and type. This project aimed to create an electronic health record (EHR)-based procedure for improving surveillance efficiency through automation of case identification. RESEARCH DESIGN AND METHODS: Youth (<20 years old) with potential evidence of diabetes (N = 8,682) were identified from EHRs at three children's hospitals participating in the SEARCH for Diabetes in Youth Study. True diabetes status/type was determined by manual chart reviews. Multinomial regression was compared with an ICD-10 rule-based algorithm in the ability to correctly identify diabetes status and type. Subsequently, the investigators evaluated a scenario of combining the rule-based algorithm with targeted chart reviews where the algorithm performed poorly. RESULTS: The sample included 5,308 true cases (89.2% type 1 diabetes). The rule-based algorithm outperformed regression for overall accuracy (0.955 vs. 0.936). Type 1 diabetes was classified well by both methods: sensitivity (Se) (>0.95), specificity (Sp) (>0.96), and positive predictive value (PPV) (>0.97). In contrast, the PPVs for type 2 diabetes were 0.642 and 0.778 for the rule-based algorithm and the multinomial regression, respectively. Combination of the rule-based method with chart reviews (n = 695, 7.9%) of persons predicted to have non-type 1 diabetes resulted in perfect PPV for the cases reviewed while increasing overall accuracy (0.983). The Se, Sp, and PPV for type 2 diabetes using the combined method were ≥0.91. CONCLUSIONS: An ICD-10 algorithm combined with targeted chart reviews accurately identified diabetes status/type and could be an attractive option for diabetes surveillance in youth.

Trends in Incidence of Type 1 and Type 2 Diabetes Among Youths - Selected Counties and Indian Reservations, United States, 2002-2015.

Diabetes is one of the most common chronic diseases among persons aged <20 years (1). Onset of diabetes in childhood and adolescence is associated with numerous complications, including diabetic kidney disease, retinopathy, and peripheral neuropathy, and has a substantial impact on public health resources (2,3). From 2002 to 2012, type 1 and type 2 diabetes incidence increased 1.4% and 7.1%, respectively, among U.S. youths (4). To assess recent trends in incidence of diabetes in youths (defined for this report as persons aged <20 years), researchers analyzed 2002-2015 data from the SEARCH for Diabetes in Youth Study (SEARCH), a U.S. population-based registry study with clinical sites located in five states. The incidence of both type 1 and type 2 diabetes in U.S. youths continued to rise at constant rates throughout this period. Among all youths, the incidence of type 1 diabetes increased from 19.5 per 100,000 in 2002-2003 to 22.3 in 2014-2015 (annual percent change [APC] = 1.9%). Among persons aged 10-19 years, type 2 diabetes incidence increased from 9.0 per 100,000 in 2002-2003 to 13.8 in 2014-2015 (APC = 4.8%). For both type 1 and type 2 diabetes, the rates of increase were generally higher among racial/ethnic minority populations than those among whites. These findings highlight the need for continued surveillance for diabetes among youths to monitor overall and group-specific trends, identify factors driving these trends, and inform health care planning.

Metabolite Profiles of Incident Diabetes and Heterogeneity of Treatment Effect in the Diabetes Prevention Program.

Novel biomarkers of type 2 diabetes (T2D) and response to preventative treatment in individuals with similar clinical risk may highlight metabolic pathways that are important in disease development. We profiled 331 metabolites in 2,015 baseline plasma samples from the Diabetes Prevention Program (DPP). Cox models were used to determine associations between metabolites and incident T2D, as well as whether associations differed by treatment group (i.e., lifestyle [ILS], metformin [MET], or placebo [PLA]), over an average of 3.2 years of follow-up. We found 69 metabolites associated with incident T2D regardless of treatment randomization. In particular, cytosine was novel and associated with the lowest risk. In an exploratory analysis, 35 baseline metabolite associations with incident T2D differed across the treatment groups. Stratification by baseline levels of several of these metabolites, including specific phospholipids and AMP, modified the effect that ILS or MET had on diabetes development. Our findings highlight novel markers of diabetes risk and preventative treatment effect in individuals who are clinically at high risk and motivate further studies to validate these interactions.

Prenatal exposure to per- and polyfluoroalkyl substances and infant growth and adiposity: the Healthy Start Study.

BACKGROUND: Prenatal exposures to certain per- and polyfluoroalkyl substances (PFAS) have been linked to lower weight and adiposity at birth but greater weight and adiposity in childhood. We hypothesized that faster growth in early infancy may be associated with maternal PFAS concentrations. METHODS: Among 415 mother-infant pairs in a longitudinal cohort study, we estimated associations between maternal pregnancy serum concentrations of six PFAS and offspring weight and adiposity at ~5 months of age, and growth in early infancy. Linear and logistic regression models were adjusted for potential confounders including maternal pre-pregnancy body mass index. Effect modification by infant sex was evaluated. We evaluated potential confounding by correlated exposures via multipollutant linear regression and elastic net penalized regression. RESULTS: Associations between maternal PFAS concentrations and infant weight and adiposity differed by offspring sex. In male infants, maternal perfluorooctanoate and perfluorononanoate were positively associated with adiposity, with percent fat mass increases of 1.5-1.7% per ln-ng/mL increase in PFAS (median adiposity at ~5 months: 24.6%). Maternal perfluorooctane sulfonate (PFOS) and perfluorohexane sulfonate (PFHxS) were associated with lower weight-for-age z-score among female infants only (-0.26 SD per ln-ng/mL PFOS, 95% CI -0.43, -0.10; -0.17 SD per ln-ng/mL PFHxS, 95% CI -0.33, -0.01). In analyses pooled by sex, 2-(N-methyl-perfluorooctane sulfonamido) acetate above vs. below the limit of detection was associated with greater odds of rapid growth in weight-for-age (odds ratio [OR] 2.2, 95% CI 1.1, 4.3) and weight-for-length (OR 3.3, 95% CI 1.8, 6.2). Multipollutant models generally confirmed the results and strengthened some associations. DISCUSSION: We observed sex- and chemical-specific associations between maternal serum PFAS concentrations and infant weight and adiposity. Multipollutant models suggested confounding by correlated PFAS with opposing effects. Although maternal PFAS concentrations are inversely associated with infant weight and adiposity at birth, rapid gain may occur in infancy, particularly in fat mass.

Apolipoprotein E-C1-C4-C2 gene cluster region and inter-individual variation in plasma lipoprotein levels: a comprehensive genetic association study in two ethnic groups.

The apolipoprotein E-C1-C4-C2 gene cluster at 19q13.32 encodes four amphipathic apolipoproteins. The influence of APOE common polymorphisms on plasma lipid/lipoprotein profile, especially on LDL-related traits, is well recognized; however, little is known about the role of other genes/variants in this gene cluster. In this study, we evaluated the role of common and uncommon/rare genetic variation in this gene region on inter-individual variation in plasma lipoprotein levels in non-Hispanic Whites (NHWs) and African blacks (ABs). In the variant discovery step, the APOE, APOC1, APOC4, APOC2 genes were sequenced along with their flanking and hepatic control regions (HCR1 and HCR2) in 190 subjects with extreme HDL-C/TG levels. The next step involved the genotyping of 623 NHWs and 788 ABs for the identified uncommon/rare variants and common tagSNPs along with additional relevant SNPs selected from public resources, followed by association analyses with lipid traits. A total of 230 sequence variants, including 15 indels were identified, of which 65 were novel. A total of 70 QC-passed variants in NHWs and 108 QC-passed variants in ABs were included in the final association analyses. Single-site association analysis of SNPs with MAF>1% revealed 20 variants in NHWs and 24 variants in ABs showing evidence of association with at least one lipid trait, including several variants exhibiting independent associations from the established APOE polymorphism even after multiple-testing correction. Overall, our study has confirmed known associations and also identified novel associations in this genomic region with various lipid traits. Our data also support the contribution of both common and uncommon/rare variation in this gene region in affecting plasma lipid profile in the general population.