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Objective: To evaluate the relation between household food insecurity (HFI) and fear of hypoglycemia among young adults with type 1 and type 2 diabetes and adolescents with type 1 diabetes and their parents., Research Design and Methods: We analyzed cross-sectional data of 1,676 young adults with youth-onset diabetes (84% type 1, 16% type 2) and 568 adolescents (<18 years old; mean age 15.1 years) with type 1 diabetes from the SEARCH for Diabetes in Youth study. Adult participants and parents of adolescent participants completed the U.S. Household Food Security Survey Module. Adults, adolescents, and parents of adolescents completed the Hypoglycemia Fear Survey, where answers range from 1 to 4. The outcomes were mean score for fear of hypoglycemia and the behavior and worry subscale scores. Linear regression models identified associations between HFI and fear of hypoglycemia scores., Results: Adults with type 1 diabetes experiencing HFI had higher fear of hypoglycemia scores (0.22 units higher for behavior, 0.55 units for worry, 0.40 units for total; all P < 0.0001) than those without HFI. No differences by HFI status were found for adolescents with type 1 diabetes. Parents of adolescents reporting HFI had a 0.18 unit higher worry score than those not reporting HFI (P < 0.05). Adults with type 2 diabetes experiencing HFI had higher fear of hypoglycemia scores (0.19 units higher for behavior, 0.35 units for worry, 0.28 units for total; all P < 0.05) than those in food secure households., Conclusions: Screening for HFI and fear of hypoglycemia among people with diabetes can help providers tailor diabetes education for those who have HFI and therefore fear hypoglycemia., (© 2023 by the American Diabetes Association.)

Objective: To project the prevalence and number of youths with diabetes and trends in racial and ethnic disparities in the U.S. through 2060., Research Design and Methods: Based on a mathematical model and data from the SEARCH for Diabetes in Youth study for calendar years 2002-2017, we projected the future prevalence of type 1 and type 2 diabetes among youth aged <20 years while considering different scenarios of future trends in incidence., Results: The number of youths with diabetes will increase from 213,000 (95% CI 209,000; 218,000) (type 1 diabetes 185,000, type 2 diabetes 28,000) in 2017 to 239,000 (95% CI 209,000; 282,000) (type 1 diabetes 191,000, type 2 diabetes 48,000) in 2060 if the incidence remains constant as observed in 2017. Corresponding relative increases were 3% (95% CI -9%; 21%) for type 1 diabetes and 69% (95% CI 43%; 109%) for type 2 diabetes. Assuming that increasing trends in incidence observed between 2002 and 2017 continue, the projected number of youths with diabetes will be 526,000 (95% CI 335,000; 893,000) (type 1 diabetes 306,000, type 2 diabetes 220,000). Corresponding relative increases would be 65% (95% CI 12%; 158%) for type 1 diabetes and 673% (95% CI 362%; 1,341%) for type 2 diabetes. In both scenarios, substantial widening of racial and ethnic disparities in type 2 diabetes prevalence are expected, with the highest prevalence among non-Hispanic Black youth., Conclusions: The number of youths with diabetes in the U.S. is likely to substantially increase in future decades, which emphasizes the need for prevention to attenuate this trend., (© 2023 by the American Diabetes Association.)

Background: The US Dietary Guidelines (USDG) form the basis of nutrition guidelines, but the research informing the 3 USDG dietary patterns (Healthy US-Style [H-US], Mediterranean [Med], and vegetarian [Veg]) has been drawn largely from observational studies among White populations., Objectives: The Dietary Guidelines 3 Diets study was a 3-arm, 12-wk randomly assigned intervention among African American (AA) adults at risk of type 2 diabetes mellitus that tested the 3 USDG dietary patterns., Methods: The AAs (ages 18-65 y, BMI 25-49.9 kg/m 2 , and BMI was measured in kg/m 2 ) with ≥3 type 2 diabetes mellitus risk factors were recruited. Weight, HbA1c, blood pressure, and dietary quality (healthy eating index [HEI]) were collected at baseline and 12 wk. In addition, participants attended weekly online classes that were designed using material from the USDG/MyPlate. Repeated measures, mixed models with maximum likelihood estimation, and robust computation of standard errors were tested., Results: Of the 227 participants screened, 63 were eligible (83% female; age 48.0 ± 10.6 y, BMI 35.9 ± 0.8 kg/m 2 ) and randomly assigned to the Healthy US-Style Eating Pattern (H-US) (n = 21, 81% completion), healthy Mediterranean-style eating pattern (Med) (n = 22, 86% completion), or healthy vegetarian eating pattern (Veg) (n = 20, 70% completion) groups. Within-group, but not between groups, weight loss was significant (-2.4 ± 0.7 kg H-US, -2.6 ± 0.7 kg Med, -2.4 ± 0.8 kg Veg; P = 0.97 between group). There was also no significant difference between groups for changes in HbA1c (0.03 ± 0.05% H-US, -0.10 ± 0.05% Med, 0.07 ± 0.06% Veg; P = 0.10), systolic BP (-5.5 ± 2.7 mmHg H-US, -3.2 ± 2.5 mmHg Med, -2.4 ± 2.9 mmHg Veg; P = 0.70), diastolic blood pressure (-5.2 ± 1.8 mmHg H-US, -2.0 ± 1.7 mmHg Med, -3.4 ± 1.9 mmHg Veg; P = 0.41), or HEI (7.1 ± 3.2 H-US, 15.2 ± 3.1 Med, 4.6 ± 3.4 Veg; P = 0.06). Post hoc analyses showed that the Med group had significantly greater improvements in HEI compared to the Veg group (difference = -10.6 ± 4.6; 95% CI: -19.7, -1.4; P = 0.02)., Conclusions: The present study demonstrates that all 3 USDG dietary patterns lead to significant weight loss among AA adults. However, none of the outcomes were significantly different between groups. This trial was registered at clinicaltrials.gov as NCT04981847., (Copyright © 2022 American Society for Nutrition. Published by Elsevier Inc. All rights reserved.)

Objective: To assess the prevalence of household food insecurity (HFI) and Supplemental Nutrition Assistance Program (SNAP) participation among youth and young adults (YYA) with diabetes overall and by type, and sociodemographic characteristics., Research Design and Methods: The study included participants with youth-onset type 1 diabetes and type 2 diabetes from the SEARCH for Diabetes in Youth study. HFI was assessed using the 18-item U.S. Household Food Security Survey Module (HFSSM) administered from 2016 to 2019; three or more affirmations on the HFSSM were considered indicative of HFI. Participants were asked about SNAP participation. We used χ2 tests to assess whether the prevalence of HFI and SNAP participation differed by diabetes type. Multivariable logistic regression models were used to examine differences in HFI by participant characteristics., Results: Of 2,561 respondents (age range, 10-35 years; 79.6% ≤25 years), 2,177 had type 1 diabetes (mean age, 21.0 years; 71.8% non-Hispanic White, 11.8% non-Hispanic Black, 13.3% Hispanic, and 3.1% other) and 384 had type 2 diabetes (mean age, 24.7 years; 18.8% non-Hispanic White, 45.8% non-Hispanic Black, 23.7% Hispanic, and 18.7% other). The overall prevalence of HFI was 19.7% (95% CI 18.1, 21.2). HFI was more prevalent in type 2 diabetes than type 1 diabetes (30.7% vs. 17.7%; P <  0.01). In multivariable regression models, YYA receiving Medicaid or Medicare or without insurance, whose parents had lower levels of education, and with lower household income had greater odds of experiencing HFI. SNAP participation was 14.1% (95% CI 12.7, 15.5), with greater participation among those with type 2 diabetes compared with those with type 1 diabetes (34.8% vs. 10.7%; P < 0.001)., Conclusions: Almost one in three YYA with type 2 diabetes and more than one in six with type 1 diabetes reported HFI in the past year-a significantly higher prevalence than in the general U.S. population., (© 2023 by the American Diabetes Association.)

Objective: We evaluated the association of household food insecurity (FI) with cognition in youth and young adults with type 1 diabetes (T1D) or type 2 diabetes (T2D)., Design: In this cross-sectional study, age-adjusted scores for composite Fluid Cognition, and sub-domain scores for Receptive Language and Inhibitory Control and Attention, were modeled stratified by diabetes-type using linear regression, with FI in the past year as the predictor, controlling for covariates. Tests for processing speed, inhibitory control/attention, working memory, episodic memory, and cognitive flexibility were administered to measure composite Fluid Cognition score. The NIHT-CB Picture Vocabulary Test was used to assess Crystallized Cognition score and rapid identification of congruent versus noncongruent items were used to assess Inhibitory Control and Attention score., Setting: The SEARCH for Diabetes in Youth study, representative of 5 U.S. states., Participants: Included 1574 youth and young adults with T1D or T2D, mean age of 21 years, mean diabetes duration of 11 years, 51% non-Hispanic white, and 47% had higher HbA1c levels (>9% HbA1c)., Results: Approximately 18% of the 1,240 participants with T1D and 31% of the 334 with T2D experienced FI. The food-insecure group with T1D had a lower composite Fluid Cognition score (β= -2.5, 95% confidence interval (CI)= -4.8, -0.1) and a lower Crystallized Cognition score (β= -3.4, CI= -5.6, -1.3) than food-secure peers. Findings were attenuated to non-significance after adjustment for demographics. Among T2D participants, no associations were observed. In participants with T1D effect modification by glycemic levels were found in the association between FI and composite Fluid Cognition score but adjustment for socioeconomic characteristics attenuated the interaction (p=0.0531)., Conclusions: Food-insecure youth and young adults with T1D or T2D did not have different cognition compared to those who were food-secure after adjustment for confounders. Longitudinal research is needed to further understand relations amongst these factors., Competing Interests: Conflicts of interest The authors declare that there is no conflict of interest regarding the publication of this article.

Aims/hypotheses: People with type 1 (T1D) or type 2 diabetes (T2D) who also have diabetes complications can have pronounced cognitive deficits. It remains unknown, however, whether and how multiple diabetes complications co-occur with cognitive dysfunction, particularly in youth-onset diabetes., Methods: Using data from the SEARCH for Diabetes in Youth study cohort, a prospective longitudinal cohort, we examined clustering of complications and their underlying clinical factors with performance on cognitive tests in young adults with youth-onset T1D or T2D. Cognition was assessed via the NIH Toolbox Cognition Battery. The main cognitive variables were age-corrected scores for composite fluid cognition and associated cognitive subdomains. Diabetes complications included retinopathy, microalbuminuria, and peripheral neuropathy (PN). Lipids, systolic blood pressure (SBP), hemoglobin A1c, and other clinical factors were included in the analyses. Clustering was applied separately to each group (T1D=646; T2D=165). A three-cluster(C) solution was identified for each diabetes type. Mean values and frequencies of all factors were compared between resulting clusters., Results: The average age-corrected score for composite fluid cognition differed significantly across clusters for each group (p<0.001). People with T1D and the lowest average fluid cognition scores had the highest frequency of self-reporting at least one episode of hypoglycemia in the year preceding cognitive testing and the highest prevalence of PN. Persons with T2D and the lowest average fluid cognition scores had the highest SBP, the highest central systolic and diastolic blood pressures, and highest prevalence of PN., Conclusions/interpretations: These findings highlight shared (PN) and unique factors (hypoglycemia in T1D; SBP in T2D) that could be targeted to potentially mitigate cognitive issues in young people with youth-onset diabetes., Competing Interests: CONFLICT OF INTEREST The authors declare no conflicts of interest.

Objective: To examine the association between household food insecurity (HFI), glycemic control, severe hypoglycemia and diabetic ketoacidosis (DKA) among youth and young adults (YYA) with youth-onset type 2 diabetes., Research Design and Methods: This cross-sectional study included 395 YYA with type 2 diabetes from the SEARCH for Diabetes in Youth Study (2015-2019). HFI was reported by young adult participants or parents of minor participants via the US Household Food Security Survey Module. Glycemic control was assessed by HbA 1c and analyzed as a continuous and categorical variable (optimal: <7.0%, suboptimal: ≥7.0%-9.0%, poor: >9.0%). Acute complications included self-reported severe hypoglycemia or DKA in the last 12 months. Adjusted logistic and linear regression were used for binary and continuous outcomes, respectively., Results: Approximately 31% reported HFI in the past 12 months. Mean HbA 1c among those with HFI was 9.2% compared to 9.5% without HFI. Of those with HFI, 56% had an HbA 1c  >9.0% compared to 55% without HFI. Adjusted models showed no associations between HFI and glycemic control. Of those with HFI, 14.4% reported experiencing DKA and 4.7% reported severe hypoglycemia. YYA with HFI had 3.08 times (95% CI: 1.18-8.06) the odds of experiencing DKA as those without HFI. There was no association between HFI and severe hypoglycemia., Conclusions: HFI was associated with markedly increased odds of DKA but not with glycemic control or severe hypoglycemia. Future research among YYA with type 2 diabetes should evaluate longitudinally whether alleviating HFI reduces DKA., (© 2022 The Authors. Pediatric Diabetes published by John Wiley & Sons Ltd.)

Background: Food insecurity (FI) rates in the United States are particularly high among households with children. This research set aims to analyze if high school students experiencing FI had higher risk for mental health and suicidal behaviors., Methods: Using combined data from 11 states that conducted the 2017 Youth Risk Behavior Survey, a total of 26,962 and 24,051 high school students were used to estimate race/ethnicity and sex-stratified prevalence ratios (PRs) from Poisson regression models. A single-question was used to measure the exposure of FI and outcomes of mental health and suicidal behaviors., Results: Overall, 10.8% of students reported FI. Students experiencing FI had increased risk for all mental health and suicide behavior outcomes, regardless of their race/ethnicity or sex. PRs ranged from 1.9 (95% confidence interval [CI]:1.8, 2.0) to 3.1 (CI: 2.7, 3.6). Among males, PRs for the association between FI and all outcomes were highest among non-Hispanic black students (PRs ranged from 2.4 [CI: 1.7, 3.2] to 5.5 [CI: 2.3, 13.3]). Among females, PRs were highest among non-Hispanic white students (PRs ranged from 1.9 [CI:1.7, 2.1] to 3.6 [CI:2.9, 4.5])., Conclusions: FI is consistently associated with mental health and suicidal behaviors among different subgroups of students., (© 2022 The Authors. Journal of School Health published by Wiley Periodicals LLC on behalf of American School Health Association.)

Adherence to the Dietary Approaches to Stop Hypertension (DASH) diet is inversely associated with type 2 diabetes mellitus (T2DM) risk. Metabolic changes due to DASH adherence and their potential relationship with incident T2DM have not been described. The objective is to determine metabolite clusters associated with adherence to a DASH-like diet in the Insulin Resistance Atherosclerosis Study cohort and explore if the clusters predicted 5-year incidence of T2DM. The current study included 570 non-diabetic multi-ethnic participants aged 40–69 years. Adherence to a DASH-like diet was determined a priori through an eighty-point scale for absolute intakes of the eight DASH food groups. Quantitative measurements of eighty-seven metabolites (acylcarnitines, amino acids, bile acids, sterols and fatty acids) were obtained at baseline. Metabolite clusters related to DASH adherence were determined through partial least squares (PLS) analysis using R. Multivariable-adjusted logistic regression was used to explore the associations between metabolite clusters and incident T2DM. A group of acylcarnitines and fatty acids loaded strongly on the two components retained under PLS. Among strongly loading metabolites, a select group of acylcarnitines had over 50 % of their individual variance explained by the PLS model. Component 2 was inversely associated with incident T2DM (OR: 0·89; (95 % CI 0·80, 0·99), P -value = 0·043) after adjustment for demographic and metabolic covariates. Component 1 was not associated with T2DM risk (OR: 1·02; (95 % CI 0·88, 1·19), P -value = 0·74). Adherence to a DASH-type diet may contribute to reduced T2DM risk in part through modulations in acylcarnitine and fatty acid physiology.

Background: Racial/ethnic health inequities have been well-documented among youth and young adults with type 1 diabetes (T1D), yet little is known about how socioeconomic position (SEP) intersects with the risk marker of race/ethnicity to predict inequities in longitudinal glycemic control., Purpose: To identify patterns of SEP, race/ethnicity, and clinical characteristics that differentiate hemoglobin A1c (HbA1c) trajectories among youth and young adults after T1D diagnosis., Methods: The SEARCH for Diabetes in Youth cohort includes youth with diabetes diagnosed from 2002 to 2006 and 2008 who were followed through 2015. We analyzed data from 1,313 youth and young adults with T1D with ≥3 HbA1c measures. Classification tree analysis identified patterns of baseline demographic, SEP, and clinical characteristic that best predicted HbA1c trajectories over an average of 8.3 years using group-based trajectory modeling., Results: Two HbA1c trajectories were identified: Trajectory 1 (77%) with lower baseline HbA1c and mild increases (from mean 7.4% to 8.4%) and Trajectory 2 (23%) with higher baseline HbA1c and major increases (from 8.5% to 11.2%). Race/ethnicity intersected with different SEP characteristics among non-Hispanic white (NHW) than in non-whites. Public health insurance predicted high-risk Trajectory 2 membership in non-whites, whereas parental education, household structure, diagnosis age and glucose checking frequency predicted membership for NHW youth and young adults. Two characteristics, race/ethnicity and parental education alone identified 80% of the Trajectory 2 members., Conclusions: Race/ethnicity intersects with multiple SEP and clinical characteristics among youth and young adults with T1D, which is associated with particularly high risk of poor long-term glycemic control., (© Society of Behavioral Medicine 2021. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.)

Background: Diabetes affects millions of people worldwide with a continued increase in incidence occurring within the pediatric population. The potential contribution of persistent organic pollutants (POPs) to diabetes in youth remains poorly known, especially regarding type 1 diabetes (T1D), generally the most prevalent form of diabetes in youth., Objectives: We investigated the associations between POPs and T1D in youth and studied the impacts of POPs on pancreatic β-cell function and viability in vitro., Methods: We used data and plasma samples from the SEARCH for Diabetes in Youth Case Control Study (SEARCH-CC). Participants were categorized as Controls, T1D with normal insulin sensitivity (T1D/IS), and T1D with insulin resistance (T1D/IR). We assessed plasma concentrations of polychlorinated biphenyls (PCBs) and organochlorine pesticides and estimated the odds of T1D through multivariable logistic regression. In addition, we performed in vitro experiments with the INS-1E pancreatic β-cells. Cells were treated with PCB-153 or p,p'-DDE at environmentally relevant doses. We measured insulin production and secretion and assessed the mRNA expression of key regulators involved in insulin synthesis (Ins1, Ins2, Pdx1, Mafa, Pcsk1/3, and Pcsk2), glucose sensing (Slc2a2 and Gck), and insulin secretion (Abcc8, Kcnj11, Cacna1d, Cacna1b, Stx1a, Snap25, and Sytl4). Finally, we assessed the effects of PCB-153 and p,p'-DDE on β-cell viability., Results: Among 442 youths, 112 were controls, 182 were classified with T1D/IS and 148 with T1D/IR. The odds ratios (OR) of T1D/IS versus controls were statistically significant for p,p'-DDE (OR 2.0, 95% confidence interval (CI) 1.0, 3.8 and 2.4, 95% CI 1.2, 5.0 for 2nd and 3rd tertiles, respectively), trans-nonachlor (OR 2.5, 95% CI 1.3, 5.0 and OR 2.3, 95% CI 1.1, 5.1 for 2nd and 3rd tertiles, respectively), and PCB-153 (OR 2.3, 95% CI 1.1, 4.6 for 3rd tertile). However, these associations were not observed in participants with T1D/IR. At an experimental level, treatment with p,p'-DDE or PCB-153, at concentrations ranging from 1 × 10 -15 M to 5 × 10 -6 M, impaired the ability of pancreatic β-cells to produce and secrete insulin in response to glucose. These failures were paralleled by impaired Ins1 and Ins2 mRNA expression. In addition, among different targeted genes, PCB-153 significantly reduced Slc2a2 and Gck mRNA expression whereas p,p'-DDE mainly affected Abcc8 and Kcnj11. While treatment with PCB-153 or p,p'-DDE for 2 days did not affect β-cell viability, longer treatment progressively killed the β-cells., Conclusion: These results support a potential role of POPs in T1D etiology and demonstrate a high sensitivity of pancreatic β-cells to POPs., (Copyright © 2022 The Authors. Published by Elsevier Ltd.. All rights reserved.)

Background: Previous studies examined the association between shopping distance, frequency, and store type separately., Objectives: The objective is to explore food acquisition and shopping habits using multidimensional measures and examine its association with body mass index (BMI)., Design: A cross-sectional study was conducted., Participants/setting: Four thousand four hundred sixty-six households from the US Food Acquisition and Purchase Survey during April 2012 to January 2013 were included in this analysis., Main Outcomes Measures: Both continuous BMI and categorical BMI were used., Statistical Analyses: Latent class analysis was used to identify the latent profiles using travel distance and perceived travel time between residential location and primary store, store type, transportation mode, and farmers' market utilization. Multivariable linear regression and multinomial logistic regression were used to assess the association between the identified patterns and continuous and categorical BMI. All analyses were stratified by urbanicity., Results: Overall, 65% (weighted percentage) of households were located in an urban tract. Thirty-seven percent were categorized as Class 1 (households that shopped more proximally, used their own vehicle, and shopped at a farmers' market), 50% as Class 2 (households that shopped more distally, used their own vehicle, and shopped at a farmers' market), and 14% as Class 3 (households that shopped proximally but perceived longer travel time, used someone else's vehicle, and did not shop at a farmers' market). Among rural households, 54% were Class 1 and 46% were Class 2 (Class 3 was not identified). Socioeconomic status characteristics, proximity, and store food price concerns were associated with the identified patterns. However, no significant association was found between the identified patterns and BMI., Conclusions: Food acquisition and shopping patterns were not associated with BMI in this national sample. However, future studies should also investigate the role of economic factors, such as food prices, in relation to shopping patterns and BMI., (Copyright © 2022 Academy of Nutrition and Dietetics. Published by Elsevier Inc. All rights reserved.)

Background: It is currently unknown if within high-quality dietary intake there exist distinct dietary patterns associated with health benefits that are identifiable with multidimensional dietary pattern analyses. The purpose of this study was to identify specific dietary patterns and groups therein and their associations with all-cause, CVD, and cancer mortality., Methods: We conducted sex-specific k-means cluster analyses within Healthy Eating Index 2015 (HEI-2015) quintile 5 in 3 US cohorts [NIH-American Association of Retired Persons Diet and Health Study (AARP), the Multiethnic Cohort (MEC), Women's Health Initiative Observational Study (WHI OS)], clusters ranging from n = 1190 to n = 12,007. Characterizations incorporated HEI-2015 overall and component-specific percentage adherence goals, using untruncated and truncated radar graphs and shape analyses. Using cohort- and sex-specific Cox proportional hazards models, associations of quintile 5 clusters with all-cause, cardiovascular disease (CVD), and cancer mortality were evaluated relative to quintile 1., Results: In each cohort sex-specific sample, 3 identified clusters included 16%-62% of participants, providing evidence for variation within high-quality dietary intake. Clusters revealed commonalities in total fruits and whole fruits intakes that exceeded goals and high sodium intake. Dairy and whole grain intakes oftentimes fell below goal. Some clusters were in addition characterized by total vegetables, greens & beans, and seafood & plant protein intakes exceeding goals. All high-quality dietary patterns were associated with a multivariable-adjusted significant 15%-26% lower risk of all-cause death than diet intake in quintile 1 (except for cluster 2 in WHI OS), and with a 16%-25% lower risk of CVD mortality in the AARP and MEC cohorts. Cancer mortality results were inconsistent., Conclusions: Multiple ways to achieve a high-quality diet were identified and significant associations with lower all-cause and CVD mortality were seen in some cohorts., (© The Author(s) 2021. Published by Oxford University Press on behalf of the American Society for Nutrition.)

This study investigated relationships between youth physical activity (PA) environments and income and non-Hispanic White population across the United States, stratified by US Census region and urban-rural designation. For all counties (n = 3142), publicly accessible data were used for sociodemographic indicators (ie, median household income and percent non-Hispanic White population) and a composite PA environment index (including exercise opportunities, violent crime incidence, walkability, and access to public schools). One-way analysis of variance was used to examine differences in PA environment index values according to income and non-Hispanic White population tertiles. There were significant differences in PA environments according to tertiles of income (F = 493.5, P < .001) and non-Hispanic White population (F = 58.6, P < .001), including variations by region and urban-rural designation. Public health practice and policy initiatives, such as joint use agreements, Safe Routes to School programs, and targeted funding allocations, should be used to address more pronounced income-based disparities in Southern and metropolitan counties and race-based disparities in rural and micropolitan counties., Competing Interests: The authors declare no conflicts of interest., (Copyright © 2021 Wolters Kluwer Health, Inc. All rights reserved.)

This study examined spatial patterns of obesogenic environments for US counties. We mapped the geographic dispersion of food and physical activity (PA) environments, assessed spatial clustering, and identified food and PA environment differences across U.S. regions and rurality categories. Substantial low food score clusters were located in the South and high score clusters in the Midwest and West. Low PA score clusters were located in the South and high score clusters in the Northeast and Midwest (p < .0001). For region, the South had significantly lower food and PA environment scores. For rurality, rural counties had significantly higher food environment scores and metropolitan counties had significantly higher PA environment scores (p < .0001). This study highlights geographic clustering and disparities in food and PA access nationwide. State and region-wide environmental inequalities may be targeted using structural interventions and policy initiatives to improve food and PA access.

Objective: To examine short-term mortality and cause of death among youth and young adults (YYAs) with youth-onset diabetes., Research Design and Methods: We included 19,717 YYAs newly diagnosed with diabetes before 20 years of age from 1 January 2002 to 31 December 2015 enrolled in the SEARCH for Diabetes in Youth Study. Of these, 14,721 had type 1; 4,141 type 2; and 551 secondary and 304 other/unknown diabetes type. Cases were linked with the National Death Index through 31 December 2017. We calculated standardized mortality ratios (SMRs) and 95% CIs based on age, sex, and race/ethnicity for state and county population areas and examined underlying causes of death., Results: During 170,148 person-years (PY) (median follow-up 8.5 years), 283 individuals died: 133 with type 1 (103.0/100,000 PY), 55 with type 2 (161.5/100,000 PY), 87 with secondary (1,952/100,000 PY), and 8 with other/unknown diabetes type (312.3/100,000 PY). SMRs (95% CI) for the first three groups were 1.5 (1.2-1.8), 2.3 (1.7-3.0), and 28.0 (22.4-34.6), respectively. Diabetes was the underlying cause of death for 42.1%, 9.1%, and 4.6% of deaths, respectively. The SMR was greater for type 2 than for type 1 diabetes ( P < 0.001). SMRs were significantly higher for individuals with type 1 diabetes who were <20 years of age, non-Hispanic White and Hispanic, and female and for individuals with type 2 diabetes who were <25 years of age, from all race/ethnic minority groups, and from both sexes., Conclusions: Excess mortality was observed among YYAs for each type of diabetes with differences in risk associated with diabetes type, age, race/ethnicity, and sex. The root causes of excess mortality among YYAs with diabetes merit further study., (© 2021 by the American Diabetes Association.)

Local-level childhood overweight and obesity data are often used to implement and evaluate community programs, as well as allocate resources to combat overweight and obesity. The most current substate estimates of US childhood obesity use data collected in 2007. Using a spatial multilevel model and the 2016 National Survey of Children's Health, we estimated childhood overweight and obesity prevalence rates at the Census regional division, state, and county levels using small-area estimation with poststratification. A sample of 24,162 children aged 10-17 years was used to estimate a national overweight and obesity rate of 30.7% (95% confidence interval: 27.0%, 34.9%). There was substantial county-to-county variability (range, 7.0% to 80.9%), with 31 out of 3,143 counties having an overweight and obesity rate significantly different from the national rate. Estimates from counties located in the Pacific region had higher uncertainty than other regions, driven by a higher proportion of underrepresented sociodemographic groups. Child-level overweight and obesity was related to race/ethnicity, sex, parental highest education (P < 0.01 for all), county-level walkability (P = 0.03), and urban/rural designation (P = 0.02). Overweight and obesity remains a vital issue for US youth, with substantial area-level variability. The additional uncertainty for underrepresented groups shows surveys need to better target diverse samples., (© The Author(s) 2021. Published by Oxford University Press on behalf of the Johns Hopkins Bloomberg School of Public Health. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.)

Background: Dyslipidemia has been documented in youth with type 2 diabetes. There is a paucity of studies examining dyslipidemia over time in youth with type 2 diabetes and associated risk factors., Objective: To evaluate lipids at baseline and follow-up and associated risk factors in youth with type 2 diabetes., Methods: We studied 212 youth with type 2 diabetes at baseline and after an average of 7 years of follow-up in the SEARCH for Diabetes in Youth Study. Abnormal lipids were defined as high-density lipoprotein cholesterol (HDL-C) < 35, low-density lipoprotein cholesterol (LDL-C) > 100, or triglycerides >150 (all mg/dl). We evaluated participants for progression to abnormal lipids (normal lipids at baseline and abnormal at follow-up), regression (abnormal lipids at baseline and normal at follow-up), stable normal, and stable abnormal lipids over time for HDL-C, LDL-C, and triglycerides. Associations between hemoglobin A1c (HbA1c) and adiposity over time (area under the curve [AUC]) with progression and stable abnormal lipids were evaluated., Results: HDL-C progressed, regressed, was stable normal, and stable abnormal in 12.3%, 11.3%, 62.3%, and 14.2% of participants, respectively. Corresponding LDL-C percentages were 15.6%, 12.7%, 42.9%, and 28.8% and triglycerides were 17.5%, 10.8%, 55.7%, and 16.0%. Each 1% increase in HbA1c AUC was associated with a 13% higher risk of progression and stable abnormal triglycerides and a 20% higher risk of progression and stable abnormal LDL-C. Higher adiposity AUC was marginally (p = 0.049) associated with abnormal HDL-C., Conclusions: Progression and stable abnormal LDL-C and triglycerides occur in youth with type 2 diabetes and are associated with higher HbA1c., (© 2021 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.)

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., (© 2021. The Author(s).)

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.

Objective: To identify correlates of hemoglobin A 1c (HbA 1c ) testing frequency and associations with HbA 1c levels and microvascular complications in youth-onset diabetes., Research Design and Methods: The SEARCH for Diabetes in Youth study collected data from individuals diagnosed with diabetes before age 20 at 8 years ( n =1,885 type 1, n =230 type 2) and 13 years ( n =649 type 1, n = 84 type 2) diabetes duration. We identified correlates of reporting ≥3 HbA 1c tests/year using logistic regression. We examined associations of HbA 1c testing with HbA 1c levels and microvascular complications (retinopathy, neuropathy, or nephropathy) using sequentially adjusted linear and logistic regression., Results: For type 1 diabetes, odds of reporting ≥3 HbA 1c tests/year at 8 and 13 years diabetes duration decreased with older age at diagnosis (odds ratio [OR] 0.91 [95% CI 0.88-0.95]), longer duration of diabetes (OR 0.90 [0.82-0.99]), not having a personal doctor (OR 0.44 [0.30-0.65]), and lapses in health insurance (OR 0.51 [0.27-0.96]). HbA 1c testing ≥3 times/year over time was associated with lower HbA 1c levels (OR -0.36% [-0.65 to -0.06]) and lower odds of microvascular complications (OR 0.64 [0.43-0.97]) at 13 years duration, but associations were attenuated after adjustment for HbA 1c testing correlates (OR -0.17 [-0.46 to 0.13] and 0.70 [0.46-1.07], respectively). For type 2 diabetes, not seeing an endocrinologist decreased the odds of reporting ≥3 HbA 1c tests/year over time (OR 0.19 [0.06-0.63]), but HbA 1c testing frequency was not associated with HbA 1c levels or microvascular complications., Conclusions: We observed disparities in HbA 1c testing frequency predominately by health care-related factors, which were associated with diabetes outcomes in type 1 diabetes., (© 2021 by the American Diabetes Association.)

Aims: To compare left ventricular structure (LV) and diastolic function in young adults with youth- onset diabetes by type, determine the prevalence of abnormal diastolic function by diabetes type using published values from age similar healthy controls, and examine the risk factors associated with diastolic function., Methods: In a cross sectional analysis we compared LV structure and diastolic function from two dimensional echocardiogram in participants with type 1 (T1D) and type 2 diabetes (T2D) who participated in the SEARCH for Diabetes in Youth Study. Linear models were used to examine the risk factors associated with worse diastolic function., Results: Of 479 participants studied, 258 had T1D (mean age 21.2 ± 5.2 years, 60.5% non-Hispanic white, 53.9% female) and 221 had T2D (mean age 24.8 ± 4.3 years, 24.4% non-Hispanic white, 73.8% female). Median diabetes duration was 11.6 years. Participants with T2D had greater LV mass index and worse diastolic function that persisted after adjustment for differences in risk factors compared with participants with T1D (all p < 0.05). Abnormal diastolic function, quantified using healthy controls, was pronounced in both groups but greater in those with T2D than T1D (T2D: 57.7% vs T1D: 47.2%, respectively), p < 0.05. Risk factors associated with worse diastolic function included older age at diabetes diagnosis, female sex, higher BP, heart rate and HbA1c and longer diabetes duration., Conclusions: LV structure and diastolic function is worse in individuals with T2D compared to T1D. However, abnormal diastolic function in seen in both groups compared to published values from age similar healthy controls.

Local environments are increasingly the focus of health behavior research and practice to reduce gaps between fruit/vegetable intake, physical activity (PA), and related guidelines. This study examined the congruency between youth food and PA environments and differences by region, rurality, and income across the United States. Food and PA environment data were obtained for all U.S. counties (N = 3142) using publicly available, secondary sources. Relationships between the food and PA environment tertiles was represented using five categories: 1) congruent-low (county falls in both the low food and PA tertiles), 2) congruent-high (county falls in both the high food and PA tertiles), 3) incongruent-food high/PA low (county falls in high food and low PA tertiles), 4) incongruent-food low/PA high (county falls in low food and high PA tertiles), and 5) intermediate food or PA (county falls in the intermediate tertile for food and/or PA). Results showed disparities in food and PA environment congruency according to region, rurality, and income (p < .0001 for each). Nearly 25% of counties had incongruent food and PA environments, with food high/PA low counties mostly in rural and low-income areas, and food low/PA high counties mostly in metropolitan and high-income areas. Approximately 8.7% of counties were considered congruent-high and were mostly located in the Northeast, metropolitan, and high-income areas. Congruent-low counties made up 10.0% of counties and were mostly in the South, rural, and low-income areas. National and regional disparities in environmental obesity determinants were identified that can inform targeted public health interventions., (Copyright © 2021. Published by Elsevier Inc.)

Objective: Poor cognition has been observed in children and adolescents with youth-onset type 1 (T1D) and type 2 diabetes (T2D) compared with control subjects without diabetes. Differences in cognition between youth-onset T1D and T2D, however, are not known. Thus, using data from SEARCH for Diabetes in Youth, a multicenter, observational cohort study, we tested the association between diabetes type and cognitive function in adolescents and young adults with T1D ( n = 1,095) or T2D ( n = 285)., Research Design and Methods: Cognition was assessed via the National Institutes of Health Toolbox Cognition Battery, and age-corrected composite Fluid Cognition scores were used as the primary outcome. Confounder-adjusted linear regression models were run. Model 1 included diabetes type and clinical site. Model 2 additionally included sex, race/ethnicity, waist-to-height ratio, diabetes duration, depressive symptoms, glycemic control, any hypoglycemic episode in the past year, parental education, and household income. Model 3 additionally included the Picture Vocabulary score, a measure of receptive language and crystallized cognition., Results: Having T2D was significantly associated with lower fluid cognitive scores before adjustment for confounders (model 1; P < 0.001). This association was attenuated to nonsignificance with the addition of a priori confounders (model 2; P = 0.06) and Picture Vocabulary scores (model 3; P = 0.49). Receptive language, waist-to-height ratio, and depressive symptoms remained significant in the final model ( P < 0.01 for all, respectively)., Conclusions: These data suggest that while youth with T2D have worse fluid cognition than youth with T1D, these differences are accounted for by differences in crystallized cognition (receptive language), central adiposity, and mental health. These potentially modifiable factors are also independently associated with fluid cognitive health, regardless of diabetes type. Future studies of cognitive health in people with youth-onset diabetes should focus on investigating these significant factors., (© 2021 by the American Diabetes Association.)

Background: Little is known about patterns of household food insecurity (HFI) across more than two time points in adults in the United States, the frequency predictors of different trajectories. The distinctions between persistent and transient food insecurity trajectories may be crucial to developing effective interventions., Objective: To characterize dominant trajectories of food security status over three time points between 2013 and 2016 and identify demographic, socioeconomic and health-related predictors of persistent and transient HFI., Design: Cohort study in disadvantaged communities in South Carolina., Setting: and subjects: 397 middle-aged participants, predominantly female, African American, living in USDA-designated food deserts., Main Outcome Measure: Household food insecurity over time using the 18-item USDA's Household Food Security Survey Module., Statistical Analyses Performed: Descriptive analyses of food security trajectories and multinomial regression analyses., Results: At baseline (2013-2014), 61% of households reported HFI during the previous 12 months, which decreased to 54% in 2015 and to 51% in 2016. Only 27% of households were persistently food secure, 36% experienced transient and 37% persistent food insecurity. Female sex (OR 2.7, 95%CI 1.2-5.9), being married or living with a partner (OR 2.4, 95CI% 1.1-5.3) and fair health status (OR 4.4, 95%CI 2.2-8.8) were associated with increased odds of persistent food insecurity. Fair health was also a significant predictor of transient food insecurity., Conclusions: These findings suggest that future research should focus on persistent versus transient trajectories separately and that tailored interventions may be needed to make progress on alleviating food insecurity among disadvantaged communities., (Copyright © 2021 Elsevier Ltd. All rights reserved.)

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 PM 2.5 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 PM 2.5 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., (Copyright © 2021 Elsevier Inc. All rights reserved.)

Effective recruitment and retention supports equitable participation in research. The aim of this article is to describe recruitment and retention methods among residents of highly disadvantaged, predominantly African American communities in the southeastern United States during the evaluation of a healthy food access initiative. We proposed that active and passive recruitment methods, intensive retention strategies, community outreach and involvement, over-enrollment to anticipate attrition, and applied principles of community participation would achieve the study's recruitment and retention goals. The enrollment goal of 560 was met at 94% (n = 527), and the retention goal of 400 was achieved (n = 408).

Objective: Health inequities persist in youth and young adults (YYA) with type 1diabetes in achieving optimal glycemic control. The purpose of this study was to assess the contribution of multiple indicators of social need to these inequities., Research Design and Methods: Two hundred and twenty two YYA withtype 1 diabetes enrolled in the SEARCH Food Insecurity Study in South Carolina and Washington between the years 2013 and 2015 were included. Latent class analysis was used to identify socioeconomic profiles based on household income, parental education, health insurance, household food insecurity, and food assistance. Profiles were evaluated in relation to glycemic control using multivariable linear and logistic regression, with HbA1c > 9%(75 mmol/mol) defined as high-risk glycemic control., Results: Two profiles were identified: a lower socioeconomic profile included YYA whose parents had lower income and/or education, and were more likely to be uninsured, receive food assistance, and be food insecure. A higher socioeconomic profile included YYA whose circumstances were opposite to those in the lower socioeconomic profile. Those with a lower socioeconomic profile were more likely to have high-risk glycemic control relative to those with a higher socioeconomic profile (OR = 2.24, 95%CI = 1.16-4.33)., Conclusions: Lower socioeconomic profiles are associated with high-risk glycemic control among YYA with type 1 diabetes. This supports recommendations that care providers of YYA with type 1 diabetes assess individual social needs in tailoring diabetes management plans to the social context of the patient., (© 2020 John Wiley & Sons A/S . Published by John Wiley & Sons Ltd.)

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., (Copyright © 2020 Elsevier Inc. All rights reserved.)

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., (© 2020 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.)

Objective : To examine diet quality and dietary intake among residents of disadvantaged neighborhoods in the Southeast United States (U.S.) and to examine associations between dietary and socioeconomic factors. Design : We examined baseline data from an evaluation study of a healthy food access initiative. Participants were recruited from two urban settings comprising seven neighborhoods of high household poverty (17% to 62%). Participants completed in-person interviews with measures of education, household income, and food security and one unannounced 24-hour dietary recall by telephone with trained registered dietitians. Food desert residence was coded based on U.S. Census data. Proportions meeting 2010 Dietary Guidelines for Americans and Healthy Eating Index 2010 (HEI-2010) scores were computed. Associations between dietary variables and participant's education, household income, food security, and food desert residence were tested. Results : Participants ( n  = 465) were predominantly African American (92%), women (80%), and overweight or obese (79%), and 52 ± 14 years of age. Sixty-three percent had low or very low food security, and 82% lived in census tracts of low income and low access to supermarkets (urban food desert). HEI-2010 scores averaged 48.8 ± 13.1. A minority of participants met dietary guidelines. Diet quality was lower among participants with lower education and among those from food insecure households ( p  < .05). Household income and food security were positively associated with meeting several dietary guidelines ( p  < .05). Food desert residence was unrelated to diet variables. Conclusions : In this disadvantaged population, significant nutritional concerns were observed, and socioeconomic factors were associated with diet quality and meeting dietary guidelines. Interventions must address broader economic, social, and policy issues such as access to affordable healthy foods.

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., (© 2020 by the American Diabetes Association.)

Aims: To evaluate cardiovascular risk factors and heart rate variability (HRV) in young adults with type 2 diabetes and arterial stiffness and to explore the relationship between HRV and arterial stiffness., Methods: We studied 185 young adults with youth-onset T2D enrolled in the SEARCH for Diabetes in Youth Study. Cardiovascular risk factors and HRV were compared between individuals with and without type 2 diabetes and arterial stiffness (defined as a pulse wave velocity greater than the 90th percentile of healthy controls, >6.767 m/s). Semiparametric regression evaluated the independent relationship between HRV and PWV., Results: Participants with T2D and arterial stiffness were more likely to be older, non-Hispanic Black, have higher systolic and diastolic blood pressure, greater adiposity and obesity-related dyslipidemia (higher triglycerides and lower HDLC). Participants with T2D and arterial stiffness also had lower overall HRV (lower SDNN) with parasympathetic loss (lower RMSSD and PNN50), p < 0.05. Lower HRV tended to be but was not significantly associated with arterial stiffness after adjustment for age, race/ethnicity, sex and cardiovascular risk factors (beta coefficient = -1.11, p = 0.08)., Conclusions: Youth with T2D and arterial stiffness have a worse cardiovascular risk profile, specifically risk factors related to the metabolic syndrome and lower HRV., Competing Interests: Declaration of competing interest The authors have no conflicts of interest to report., (Copyright © 2020 Elsevier Inc. All rights reserved.)

Background: Diverse environmental factors are associated with physical activity (PA) and healthy eating (HE) among youth. However, no study has created a comprehensive obesogenic environment index for children that can be applied at a large geographic scale. The purpose of this study was to describe the development of a childhood obesogenic environment index (COEI) at the county level across the United States., Methods: A comprehensive search of review articles (n = 20) and input from experts (n = 12) were used to identify community-level variables associated with youth PA, HE, or overweight/obesity for potential inclusion in the index. Based on strength of associations in the literature, expert ratings, expertise of team members, and data source availability, 10 key variables were identified - six related to HE (# per 1000 residents for grocery/superstores, farmers markets, fast food restaurants, full-service restaurants, and convenience stores; as well as percentage of births at baby (breastfeeding)-friendly facilities) and four related to PA (percentage of population living close to exercise opportunities, percentage of population < 1 mile from a school, a composite walkability index, and number of violent crimes per 1000 residents). Data for each variable for all counties in the U.S. (n = 3142) were collected from publicly available sources. For each variable, all counties were ranked and assigned percentiles ranging from 0 to 100. Positive environmental variables (e.g., grocery stores, exercise opportunities) were reverse scored such that higher values for all variables indicated a more obesogenic environment. Finally, for each county, a total obesogenic environment index score was generated by calculating the average percentile for all 10 variables., Results: The average COEI percentile ranged from 24.5-81.0 (M = 50.02,s.d. = 9.01) across US counties and was depicted spatially on a choropleth map. Obesogenic counties were more prevalent (F = 130.43,p < .0001) in the South region of the U.S. (M = 53.0,s.d. = 8.3) compared to the Northeast (M = 43.2,s.d. = 6.9), Midwest (M = 48.1,s.d. = 8.5), and West (M = 48.4,s.d. = 9.8). When examined by rurality, there were also significant differences (F = 175.86,p < .0001) between metropolitan (M = 46.5,s.d. = 8.4), micropolitan (M = 50.3,s.d. = 8.1), and rural counties (M = 52.9,s.d. = 8.8) across the U.S., Conclusion: The COEI can be applied to benchmark obesogenic environments and identify geographic disparities and intervention targets. Future research can examine associations with obesity and other health outcomes.

A quasi-experiment evaluated a food hub's (FH) impact in a low-income/low-access (food desert) setting on fruit and vegetable (F&V) intake, diet quality, kilocalories, perceived food environment, BMI, and farmers' market shopping versus a matched community (n = 265 FH, n = 262 Comparison). Comparison shoppers had better baseline perceptions of their food environment, but FH shoppers improved significantly more than Comparison shoppers. Comparison shoppers significantly increased F&V intake versus FH shoppers. Effects were not significant for other diet outcomes, BMI, or farmers' market shopping. Factors besides spacial access to healthy food need consideration to address dietary intake and obesity in disadvantaged communities., Competing Interests: Declaration of competing interest None., (Copyright © 2020 Elsevier Ltd. All rights reserved.)

Central obesity may contribute to the development of hypertension in youths with diabetes. The SEARCH for Diabetes in Youth Study followed 1518 youths with type 1 diabetes (T1D) and 177 with type 2 diabetes (T2D) diagnosed when <20 years of age for incident hypertension. Incident hypertension was defined as blood pressure ≥95th percentile (or ≥130/80 mm Hg) or reporting antihypertensive therapy among those without hypertension at baseline. Poisson regression models were stratified by diabetes type and included demographic and clinical factors, clinical site, and waist-to-height ratio (WHtR). Youths with T2D were more likely to develop hypertension than those with T1D (35.6% vs 14.8%, P < .0001). For each 0.01 unit of annual increase in WHtR, adjusted relative risk for hypertension was 1.53 (95% CI 1.36-1.73) and 1.20 (95% CI 1.00-1.43) for youths with T1D and T2D, respectively. Effective strategies targeted toward reducing central obesity may reduce hypertension among youths with diabetes., (© 2020 The Authors. The Journal of Clinical Hypertension published by Wiley Periodicals LLC.)

Stressful life changes may tax people's adaptive capacity. We sought to determine if and when experiences of stressful life changes were associated with increased odds of adverse nutrition-related health outcomes among US Army soldiers relative to those who did not experience the same stressful life change. An additional aim was to determine which stressful life changes had the greatest association with these outcomes and if there were gender differences in the magnitude of the associations. Stressful life changes studied included: changes in marital status, combat deployment or return from deployment, relocation, adding a child, change in rank, change in occupation, and development of a physical limitation to duty. Using longitudinal data from the Stanford Military Data Repository, which represents all active-duty soldiers aged 17-62 between 2011 and 2014 (n = 827,126), we employed an event history analysis to examine associations between stressful life changes and a subsequent diagnosis of hyperlipidemia, substantial weight gain, and weight-related separation from the Army. Marriage was associated with an increase in the odds of substantial weight gain 3 months later for both men and women. Developing a physical duty limitation was associated with an increase in the odds of a hyperlipidemia diagnosis 2 months later for both men and women, as was substantial weight gain 2 months later. Stressful life changes were also associated with increased odds of nutrition-related health outcomes, although we found gender differences in the magnitude of the associations. Findings could be used to mitigate the effects of stress on health by health professionals.

Traditionally, nutritional epidemiologists have utilized single nutrient or dietary pattern approaches to examine diet-health relationships. However, the former ignores that nutrients are consumed from foods within dietary patterns, and, conversely, dietary patterns may provide little information on mechanisms of action. Substitution provides a framework for estimating diet-health relationships while holding some nutrient intakes constant. We examined substitution effects of polyunsaturated fatty acids (PUFAs) in the SEARCH Nutrition Ancillary Study in the context of food group source. PUFAs were calculated from fatty acids 18:3, 20:5, and 22:6 ( n -3), and 18:2 and 20:4 ( n -6) from a food frequency questionnaire, quantified by food group. Models were adjusted for other fat intake, carbohydrates, protein, age, race, gender, and diabetes duration. Participants ( n = 1441) were 14 years old on average, 51% female, with type 1 diabetes for 3.6 years. Mean intake of PUFAs was 14.9 g/day, and the highest PUFA sources were nonsolid fats, nuts, grains, red/processed meats, sweets/desserts, and high-fat chicken. PUFAs from nuts were inversely associated with low-density lipoprotein cholesterol (LDL) ( p = 0.03) and PUFAs from high-fat chicken were positively associated with LDL ( p < 0.01). Substituting nuts for chicken was associated with -7.4 mg/dL in LDL. These findings illustrate the importance of considering food group-based sources of nutrients when examining diet-health relationships.

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 PM 2.5 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 PM 2.5 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 PM 2.5 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., (Copyright © 2019 The Authors. Published by Elsevier Ltd.. All rights reserved.)

Objective: We explored how positive and negative life experiences of caregivers are associated with household food insecurity., Design: The Midlands Family Study (MFS) was a cross-sectional study with three levels of household food security: food secure, food insecure without child hunger and food insecure with child hunger. Ordinal logistic regression analysis was used for analyses of negative and positive life experiences (number, impact, type) associated with food insecurity., Setting: An eight-county region in South Carolina, USA, in 2012-2013., Participants: Caregivers (n 511) in households with children., Results: Caregivers who reported greater numbers of negative life experiences and greater perceived impact had increased odds of household food insecurity and reporting their children experienced hunger. Each additional negative life experience count of the caregiver was associated with a 16 % greater odds of food insecurity without child hunger and a 28 % greater odds of child hunger. Each one-unit increase in the negative impact score (e.g. a worsening) was associated with 8 % higher odds of food insecurity without child hunger and 12 % higher odds of child hunger. Negative work experiences or financial instability had the strongest association (OR = 1·8; 95 % CI 1·5, 2·2) with child hunger. Positive life experiences were generally not associated with food security status, with one exception: for each unit increase in the number of positive experiences involving family and other relationships, the odds of child hunger decreased by 22 %., Conclusions: More research is needed to understand approaches to build resilience against negative life experiences and strengthen positive familial, community and social relationships.

The relationship between added sugar and arterial stiffness in youth with type 1 diabetes (T1D) has not been well-described. We used data from the SEARCH for Diabetes in Youth Study (SEARCH), an ongoing observational cohort study, to determine the association between added sugar and arterial stiffness in individuals diagnosed with T1D <20 years of age ( n = 1539; mean diabetes duration of 7.9 ± 1.9 years). Added sugar intake was assessed by a food frequency questionnaire, and arterial stiffness measures included pulse wave velocity (PWV) and augmentation index. Separate multivariate linear regression models were used to evaluate the association between added sugar and arterial stiffness. Separate interaction terms were included to test for effect modification by body mass index (BMI) z-score and physical activity (PA). Overall, there was no association between added sugar and arterial stiffness ( P > 0.05); however, the association between added sugar and arterial stiffness differed by BMI z-score ( P for interaction = 0.003). For participants with lower BMI z-scores, added sugar intake was positively associated with PWV trunk measurements, whereas there was no association for those who had a higher BMI z-score. PA did not significantly modify the association between added sugar and arterial stiffness. Further research is needed to determine the longitudinal relationship and to confirm that obesity differentially affects this association.

Affordability and geographic accessibility are key health care access characteristics. We used data from 481 youth and young adults (YYA) with diabetes (389 type 1, 92 type 2) to understand the association between health care access and glycemic control as measured by HbA 1c values. In multivariate models, YYA with state or federal health insurance had HbA 1c percentage values 0.68 higher (P = 0.0025) than the privately insured, and those without insurance 1.34 higher (P < 0.0001). Not having a routine diabetes care provider was associated with a 0.51 higher HbA 1c (P = 0.048) compared to having specialist care, but HbA 1c did not differ significantly (P = 0.069) between primary vs specialty care. Distance to utilized provider was not associated with HbA 1c among YYA with a provider (P = 0.11). These findings underscore the central role of health insurance and indicate a need to better understand the root causes of poorer glycemic control in YYA with state/federal insurance., (© 2019 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.)

Career mentoring is beneficial for mobility, growth and development at all stages of an epidemiologist's career. The American College of Epidemiology (ACE) provides a variety of opportunities to be mentored and to mentor, facilitated through the Career Mentoring Committee. ACE has now moved to a new level of engagement in mentoring, offering a more inclusive and structured one-on-one mentoring program for epidemiologists to achieve their professional goals. This program has recently been formalized in the Mentoring Guidelines that were developed by the Career Mentoring Committee. The Mentoring Guidelines can be used as a resource for both mentee and mentor as they offer suggestions for specific areas for mentoring and guiding principles of the mentee - mentor relationship. It is the hope of the Career Mentoring Committee and ACE that the adoption of the mentoring program will contribute positively to the professional success of ACE members at various career stages and in various career paths., (Copyright © 2019 Elsevier Inc. All rights reserved.)

Establishing the shape and determinants of trajectories of body mass index (BMI) among Soldiers is critical given the importance of weight management to military service requirements. To establish the shape and determinants of BMI trajectories among Soldiers, we aimed to (1) model the overall BMI trajectory of Soldiers, (2) find the most common trajectory groups among Soldiers, (3) investigate the relationship between BMI trajectories and sociodemographic and military-specific characteristics, and (4) determine if there were Soldiers with large fluctuations in BMI. The study population included all US Army Soldiers on active-duty between 2011 and 2014 who were age 17-62 ( n  = 827,126). With longitudinal data from the Stanford Military Data Repository, we used group-based trajectory modeling to identify the BMI trajectories of Soldiers and multinomial logistic regression to estimate associations between Soldier characteristics and trajectory membership. Four distinct BMI trajectory groups were found: increasing, decreasing, constant, and inconstant. The constant, increasing, and decreasing trajectories were similar in shape and percentage between men and women. The constant trajectory had the fewest Soldiers who exceeded weight standards or had duty limitations. The increasing trajectory was associated with marriage and fewer service years. The decreasing trajectory was associated with more service years and higher educational attainment. The inconstant trajectory differed in shape between men and women. Over 6% of men and 12% of women had fluctuations in BMI indicative of weight cycling. Understanding the characteristics associated with BMI trends may assist the Army in targeting resources aimed to improve Soldier health and combat readiness.

Objective: To examine how point-of-sale (POS) display bans, tobacco retailer density and tobacco retailer proximity were associated with smoking cessation and relapse in a cohort of smokers in Canada, where provincial POS bans were implemented differentially over time from 2004 to 2010., Methods: Data from the 2005 to 2011 administrations of the International Tobacco Control (ITC) Canada Survey, a nationally representative cohort of adult smokers, were linked via residential geocoding with tobacco retailer data to derive for each smoker a measure of retailer density and proximity. An indicator variable identified whether the smoker's province banned POS displays at the time of the interview. Outcomes included cessation for at least 1 month at follow-up among smokers from the previous wave and relapse at follow-up among smokers who had quit at the previous wave. Logistic generalised estimating equation models were used to determine the relationship between living in a province with a POS display ban, tobacco retailer density and tobacco retailer proximity with cessation (n=4388) and relapse (n=866)., Results: Provincial POS display bans were not associated with cessation. In adjusted models, POS display bans were associated with lower odds of relapse which strengthened after adjusting for retailer density and proximity, although results were not statistically significant (OR 0.66, 95% CI 0.41 to 1.07, p=0.089). Neither tobacco retailer density nor proximity was associated with cessation or relapse., Conclusions: Banning POS retail displays shows promise as an additional tool to prevent relapse, although these results need to be confirmed in larger longitudinal studies., Competing Interests: Competing interests: None declared., (© Article author(s) (or their employer(s) unless otherwise stated in the text of the article) 2019. All rights reserved. No commercial use is permitted unless otherwise expressly granted.)

Excess adiposity is common in youth with type 1 diabetes, yet little is known about the sociodemographic factors that predict longitudinal trajectories of body fat. We analyzed data from 363 females and 379 males with type 1 diabetes over ~9 years of follow-up (mean baseline age 12.8 ± 2.3 years in females, 13.2 ± 2.4 years in males). Estimated body fat percentage (eBFP) was calculated with validated sex- and race/ethnicity-specific equations. Group-based modeling identified three eBFP trajectories for each sex. All female trajectories showed gradual increases, while male trajectories showed gradual decreases (<5% in eBFP) that plateaued around 7 years of diabetes duration. Female trajectories showed differences in baseline eBFP: Group F1 (38.0%), mean eBFP 27.8 ± 3.0%: Group F2 (47.9%), mean eBFP 33.9 ± 3.0%: and Group F3 (14.1%), mean eBFP 41.7 ± 4.1%. Male trajectories also showed differences in baseline eBFP: Group M1 (57.2%), mean eBFP 22.0 ± 3.0%: Group M2 (30.9%), mean eBFP 33.9 ± 3.0%: and Group M3 (12.9%), mean eBFP 36.1 ± 3.7%. In multinomial models, adjusted for clinical factors (eg, insulin regimen, insulin dose, and hemoglobin A1c), females who reported a single-parent household (adjusted odds ratio [aOR] = 3.34, 95% confidence interval [CI]: 1.49, 7.47), parental education of less than a college degree (aOR = 3.79, 95% CI: 1.60, 9.60), and a lack of private health insurance (aOR = 3.74, 95% CI: 1.45, 9.60), and a household income of less than $75 000 per year (aOR = 3.13, 95% CI: 1.27, 7.70) were approximately three to four times more likely to be in the highest eBFP trajectory group relative to the lowest eBFP trajectory group. Males who reported a household income of <$75 000/year were almost twice as likely to be in the Group M3 than the Group M1 in the unadjusted model only (aOR = 1.79, 95% CI: 0.91, 4.01 vs unadjusted OR: 2.48, 95% CI: 1.22, 5.06). Lower socioeconomic status may be associated with excess body fat throughout adolescence in type 1 diabetes, particularly among females., (© 2018 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.)

Background: Little is known about the food acquisition and shopping habits of residents living in food deserts., Objective: To identify distinct food acquisition and shopping patterns among residents, most of whom (81%) live in food desert (low income and low access) census tracts, and characterize these patterns with respect to the residents' socioeconomic status, nutrition knowledge, and perceptions of their food environment., Design: This is a cross-sectional study., Participants/setting: Four hundred sixty-six primary food shoppers were included from two counties in South Carolina during 2013-2014., Main Outcome Measures: Participants' self-reported food acquisition and shopping habits, including shopping distance; frequency; store type; transportation mode; use of farmers' markets, food banks/pantries, and church/social service organizations, were used to develop shopping patterns and group residents. Supplemental Nutrition Assistance Program participation, food security, income, and education, nutrition knowledge, and perceptions of the food environment were used to characterize these groups., Statistical Analyses Performed: Latent class analysis and multinomial logistic regression were used to identify and characterize patterns, respectively., Results: Three patterns were identified, including those who use community food resources, are infrequent grocery shoppers, and use someone else's car or public transportation when shopping (Class 1) (35%), those who use community food resources and are more frequent and proximal shoppers (Class 2) (41%), and those who do not use community food resources and are distal shoppers (Class 3) (24%). Compared with Class 3, Class 1 had comparatively lower socioeconomic status. Class 2 also had comparatively lower socioeconomic attributes except for income. Class 2 was not significantly different from Class 1 except that a higher proportion in Class 1 saw food access as a problem. No significant differences across classes were found regarding fruit and vegetable recommendation knowledge., Conclusions: Shopping frequency, use of community food resources, transportation methods, and shopping distance were the key factors that defined distinct patterns among residents living in low-income areas. Future interventions to increase healthy food access in underserved areas should not only consider accessibility but also community food resource use., (Copyright © 2018 Academy of Nutrition and Dietetics. Published by Elsevier Inc. All rights reserved.)