Self-Reported Food Security in Adolescents with Type 1 Diabetes: Association with Hemoglobin A1c and Mental Health Symptoms Independent of Household Food Security.

BACKGROUND: Typically, child exposure to food insecurity is assessed by caregiver reports of household food security. Child report has the potential for greater accuracy because it pertains only to the child whose experiences may differ from caregiver reports. OBJECTIVE: We assessed if adolescent-reported food insecurity was associated with levels of hemoglobin A1c (HbA1c), acute diabetes-related complications, depressive symptoms, and disordered eating behaviors in adolescents with type 1 diabetes, independently from household food security. METHODS: In a cross-sectional analysis of the multicenter SEARCH for Diabetes in Youth Cohort Study (phase 4, 2016-2019) including 601 adolescents aged 10-17 y with type 1 diabetes and their caregivers, household food security, and adolescent-reported food security were assessed using the 18-item Household Food Security Survey Module and the 6-item Child Food Security Assessment questionnaire. Age-stratified (10-13 and 14-17) regression models were performed to estimate independent associations, adjusting for sociodemographics, clinical factors, and household food security. RESULTS: Food insecurity was reported by 13.1% (n = 79) of adolescents and 15.6% (n = 94) of caregivers. Among adolescent-caregiver dyads, 82.5% (n = 496) of reports were concordant and 17.5% (n = 105) discordant, Cohen's κ= 0.3. Adolescent-reported food insecurity was not independently associated with HbA1c, diabetic ketoacidosis, and severe hypoglycemia, including in age-stratified analyses. Adolescent-reported food insecurity was independently associated with elevated odds of depressive symptoms [odds ratio (OR): 3.6; 95% confidence interval (CI): 1.3, 10.3] and disordered eating behaviors (OR: 2.5, 95% CI: 1.4, 4.6) compared with adolescents reporting food security; these associations remained in both age groups for disordered eating behaviors and in the older group for depressive symptoms. CONCLUSIONS: Adolescents with type 1 diabetes may experience food insecurity differently than caregivers. Adolescent-reported food insecurity was independently associated with depressive symptoms and disordered eating behaviors and thus may be an important attribute to assess in addition to household food security in adolescents with type 1 diabetes.

Properties of the Household Food Security Survey Module Scale in Young Adults with Diabetes.

BACKGROUND: The Household Food Security Survey Module (HFSSM) was not tailored to people with chronic diseases or young adults (YAs). OBJECTIVES: We aim to evaluate whether the 18-item HFSSM meets assumptions underlying the scale among YAs with diabetes. METHODS: Data from 1887 YAs with youth-onset type 1 diabetes or type 2 diabetes were used from the SEARCH for Diabetes in Youth Study, 2016-2019, and on 925 who returned for the SEARCH Food Security Cohort Study, 2018-2021, all of whom had completed the HFSSM. Guttman scaling properties (affirmation of preceding less severe items) and Rasch model properties (probability to answer an item based on difficulty level) were assessed. RESULTS: Items 3 (balanced meals) and 6 (eating less than one should) were affirmed more frequently than expected (nonmonotonic response pattern). At 1.2%-3.5%, item nonresponse was rare among type 1 diabetes but higher among type 2 diabetes (range: 3.1%-10.6%). Items 9 (not eating the whole day) and 3 did not meet the Guttman scaling properties. Rasch modeling revealed that item 3 had the smallest difficulty parameter. INFIT indices suggested that some responses to item 3 did not match the pattern in the rest of the sample. Classifying household food insecurity (HFI) based on items 1 and 2 compared with other 2-item combinations, including item 3, revealed a substantial undercount of HFI ranging from 5% to 8% points. CONCLUSIONS: Use of the HFSSM among YAs with diabetes could potentially result in biased HFI reporting and affect estimates of HFI prevalence in this population.

Developing an automated algorithm for identification of children and adolescents with diabetes using electronic health records from the OneFlorida+ clinical research network.

AIM: To develop an automated computable phenotype (CP) algorithm for identifying diabetes cases in children and adolescents using electronic health records (EHRs) from the UF Health System. MATERIALS AND METHODS: The CP algorithm was iteratively derived based on structured data from EHRs (UF Health System 2012-2020). We randomly selected 536 presumed cases among individuals aged <18 years who had (1) glycated haemoglobin levels ≥ 6.5%; or (2) fasting glucose levels ≥126 mg/dL; or (3) random plasma glucose levels ≥200 mg/dL; or (4) a diabetes-related diagnosis code from an inpatient or outpatient encounter; or (5) prescribed, administered, or dispensed diabetes-related medication. Four reviewers independently reviewed the patient charts to determine diabetes status and type. RESULTS: Presumed cases without type 1 (T1D) or type 2 diabetes (T2D) diagnosis codes were categorized as non-diabetes/other types of diabetes. The rest were categorized as T1D if the most recent diagnosis was T1D, or otherwise categorized as T2D if the most recent diagnosis was T2D. Next, we applied a list of diagnoses and procedures that can determine diabetes type (e.g., steroid use suggests induced diabetes) to correct misclassifications from Step 1. Among the 536 reviewed cases, 159 and 64 had T1D and T2D, respectively. The sensitivity, specificity, and positive predictive values of the CP algorithm were 94%, 98% and 96%, respectively, for T1D and 95%, 95% and 73% for T2D. CONCLUSION: We developed a highly accurate EHR-based CP for diabetes in youth based on EHR data from UF Health. Consistent with prior studies, T2D was more difficult to identify using these methods.

Nutrition in adolescent growth and development.

During adolescence, growth and development are transformative and have profound consequences on an individual's health in later life, as well as the health of any potential children. The current generation of adolescents is growing up at a time of unprecedented change in food environments, whereby nutritional problems of micronutrient deficiency and food insecurity persist, and overweight and obesity are burgeoning. In a context of pervasive policy neglect, research on nutrition during adolescence specifically has been underinvested, compared with such research in other age groups, which has inhibited the development of adolescent-responsive nutritional policies. One consequence has been the absence of an integrated perspective on adolescent growth and development, and the role that nutrition plays. Through late childhood and early adolescence, nutrition has a formative role in the timing and pattern of puberty, with consequences for adult height, muscle, and fat mass accrual, as well as risk of non-communicable diseases in later life. Nutritional effects in adolescent development extend beyond musculoskeletal growth, to cardiorespiratory fitness, neurodevelopment, and immunity. High rates of early adolescent pregnancy in many countries continue to jeopardise the growth and nutrition of female adolescents, with consequences that extend to the next generation. Adolescence is a nutrition-sensitive phase for growth, in which the benefits of good nutrition extend to many other physiological systems.

A 12-Week Randomized Intervention Comparing the Healthy US, Mediterranean, and Vegetarian Dietary Patterns of the US Dietary Guidelines for Changes in Body Weight, Hemoglobin A1c, Blood Pressure, and Dietary Quality among African American Adults.

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/m2, and BMI was measured in kg/m2) 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/m2) 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.

Diabetes complications and cognitive function in young adults with youth-onset type 1 or type 2 diabetes: the SEARCH for Diabetes in Youth Study.

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.

Household Food Insecurity and Cognition in Youth and Young Adults with Youth-Onset Diabetes.

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 (ß= -2.5, 95% confidence interval (CI)= -4.8, -0.1) and a lower Crystallized Cognition score (ß= -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.

Variations in Dietary Patterns Defined by the Healthy Eating Index 2015 and Associations with Mortality: Findings from the Dietary Patterns Methods Project.

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.

Inequalities in Glycemic Control in Youth with Type 1 Diabetes Over Time: Intersectionality Between Socioeconomic Position and Race and Ethnicity.

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.

Metabolomic profiling of the Dietary Approaches to Stop Hypertension diet provides novel insights for the nutritional epidemiology of type 2 diabetes mellitus.

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 40­69 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.

Household food insecurity is associated with diabetic ketoacidosis but not severe hypoglycemia or glycemic control in youth and young adults with youth-onset type 2 diabetes.

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 HbA1c 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 HbA1c among those with HFI was 9.2% compared to 9.5% without HFI. Of those with HFI, 56% had an HbA1c >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.

Exploring Disparities in Youth Physical Activity Environments by Income and Non-Hispanic White Population Across the United States.

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.

Estimates of Childhood Overweight and Obesity at the Region, State, and County Levels: A Multilevel Small-Area Estimation Approach.

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.

A cross sectional study to compare cardiac structure and diastolic function in adolescents and young adults with youth-onset type 1 and type 2 diabetes: The SEARCH for Diabetes in Youth Study.

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.

Incongruency of youth food and physical activity environments in the United States: Variations by region, rurality, and income.

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.

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.

Glycemic control is associated with dyslipidemia over time in youth with type 2 diabetes: The SEARCH for diabetes in youth study.

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.

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

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

Persistence and transience of food insecurity and predictors among residents of two disadvantaged communities in South Carolina.

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.

Recruitment and Retention for the Evaluation of a Healthy Food Initiative in Economically Disadvantaged, Majority African American Communities.

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).