scholarly journals 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

2021 ◽  
Vol 20 (1) ◽  
Author(s):  
Amy S. Shah ◽  
Scott Isom ◽  
Dana Dabelea ◽  
Ralph D’Agostino ◽  
Lawrence M. Dolan ◽  
...  
Keyword(s):  
Risk Factors ◽  
Diastolic Function ◽  
Healthy Controls ◽  
Cross Sectional ◽  
Factors Associated ◽  
Youth Study ◽  
Hispanic White ◽  
Diabetes In Youth

Abstract 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.

scholarly journals Prevalence of and Risk Factors for Diabetic Peripheral Neuropathy in Youth With Type 1 and Type 2 Diabetes: SEARCH for Diabetes in Youth Study

Diabetes Care ◽  
2017 ◽  
Vol 40 (9) ◽  
pp. 1226-1232 ◽  
Author(s):  
Mamta Jaiswal ◽  
Jasmin Divers ◽  
Dana Dabelea ◽  
Scott Isom ◽  
Ronny A. Bell ◽  
...  
Keyword(s):  
Risk Factors ◽  
Type 2 Diabetes ◽  
Peripheral Neuropathy ◽  
Diabetic Peripheral Neuropathy ◽  
Youth Study ◽  
Diabetes In Youth

279-OR: Cognition in Young Adults with Youth-Onset Type 1 and Type 2 Diabetes: The SEARCH for Diabetes in Youth Study

Diabetes ◽  
2020 ◽  
Vol 69 (Supplement 1) ◽  
pp. 279-OR
Author(s):  
ALLISON SHAPIRO ◽  
DANA DABELEA ◽  
JEANETTE M. STAFFORD ◽  
RALPH DAGOSTINO ◽  
CATHERINE PIHOKER ◽  
...  
Keyword(s):  
Type 2 Diabetes ◽  
Young Adults ◽  
Onset Type ◽  
Youth Study ◽  
Diabetes In Youth

scholarly journals Factors Associated with Poor Glycemic and Lipid Levels in Ambulatory Diabetes Mellitus Type 2 Patients in Asmara, Eritrea: A Cross-Sectional Study

2020 ◽  
Vol 2020 ◽  
pp. 1-12 ◽  
Author(s):  
Oliver Okoth Achila ◽  
Millen Ghebretinsae ◽  
Abraham Kidane ◽  
Michael Simon ◽  
Shewit Makonen ◽  
...  
Keyword(s):  
Diabetes Mellitus ◽  
Risk Factors ◽  
Waist Circumference ◽  
Cross Sectional Study ◽  
Sectional Study ◽  
Cross Sectional ◽  
Factors Associated ◽  
Specific Lipid

Objective. There is a dearth of relevant research on the rapidly evolving epidemic of diabetes mellitus (particularly Type 2 diabetes mellitus) in sub-Saharan Africa. To address some of these issues in the Eritrean context, we conducted a cross-sectional study on glycemic and lipid profiles and associated risk factors. Methods. A total of 309 patients with diabetes mellitus on regular follow-up at the Diabetic and Hypertensive Department at Halibet Regional Referral Hospital, Asmara, were enrolled for the study. Data on specific clinical chemistry and anthropomorphic parameters was collected. Chi-squared (χ2) test or Fischer’s exact test was used to evaluate the relationship between specific variables. Multivariate logistic regression (backward: conditional) was undertaken to identify the factors associated with increased odds of suboptimal values in glucose and specific lipid panel subfractions. Results. High proportions of patients (76.7%) had suboptimal levels of HbA1c with a mean±SD of 8.6%±1.36, respectively. In multivariate regression analysis, the likelihood of HbA1c≥7% was higher in patients with abnormal WHR (AOR=3.01, 95% CI, 3.01 (1.15–7.92=0.024)) and in patients without hypertension (AOR=1.97, 95% CI (1.06–3.56), p=0.021). A unit reduction in eGFR was also associated with HbA1c≥7% (AOR=0.99, 95% CI (0.98–1=0.031)). In a separate analysis, the data shows that 80.9% of the patients had dyslipidemia. In particular, 62.1% of the patients had TC≥200 mg/dL (risk factors: sex, hypertension, and HbA1c concentration), 81.6% had LDL‐C≥100 mg/dL (risk factors: sex and hypertension), 56.3% had TG≥150 (risk factors: sex, HbA1c, and waist circumference), 62.8% had abnormal HDL-C (risk factors: waist circumference), 78.3% had non‐HDL<130 mg/dL (risk factors: duration of disease, reduced estimated glomerular filtration rate, and HbA1c), and 45.3% had abnormal TG/HDL (risk factors: sex, age of patient, FPG, and waist circumference). Conclusions. The quality of care, as measured by glycemic and specific lipid targets, in this setting is suboptimal. Therefore, there is an urgent need for simultaneous improvements in both indicators. This will require evidence-based optimization of pharmacological and lifestyle interventions. Therefore, additional studies, preferably longitudinal studies with long follow-up, are required on multiple aspects of DM.

scholarly journals Detection of Diabetes Status and Type in Youth using Electronic Health Records (EHRs): The SEARCH for Diabetes in Youth Study

2020 ◽  
Author(s):  
Brian J. Wells ◽  
Kristin M. Lenoir ◽  
Lynne E. Wagenknecht ◽  
Elizabeth J. Mayer-Davis ◽  
Jean M. Lawrence ◽  
...  
Keyword(s):  
Type 2 Diabetes ◽  
Type 1 Diabetes ◽  
Multinomial Regression ◽  
Rule Based ◽  
Diabetes Status ◽  
Icd 10 ◽  
Youth Study ◽  
Diabetes In Youth

<u>Objective:</u> 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. <p><u> </u></p> <p><u>Research Design and Methods:</u> Youth (< 20 years) 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.</p> <p> </p> <p><u>Results:</u> The sample included 5308 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 (<i>Se</i>) (>0.95), specificity (<i>Sp</i>) (>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. Combining 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 sensitivity, specificity, and PPV for type 2 diabetes using the combined method were >=0.91. </p> <p> </p> <p><u>Conclusions</u>: 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. </p> <br>

scholarly journals Prevalence and Predictors of Household Food Insecurity and Supplemental Nutrition Assistance Program Use in Youth and Young Adults With Diabetes: The SEARCH for Diabetes in Youth Study

2021 ◽  
Author(s):  
Faisal S. Malik ◽  
Angela D. Liese ◽  
Beth A. Reboussin ◽  
Katherine A. Sauder ◽  
Edward A. Frongillo ◽  
...  
Keyword(s):  
Type 2 Diabetes ◽  
Type 1 Diabetes ◽  
Assistance Program ◽  
Household Food ◽  
Youth And Young Adults ◽  
Nutrition Assistance ◽  
Youth Study ◽  
Hispanic White

<a>OBJECTIVES: To assess the prevalence of household food insecurity (HFI) and Supplemental Nutrition Assistance Program (SNAP) participation in youth and young adults (YYA) with diabetes overall, by type, and sociodemographic characteristics.</a> <p>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 2016-2019; ³3 affirmations on the HFSSM were considered indicative of HFI. Participants were asked about SNAP participation. Chi-square tests were used 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. </p> <p>RESULTS: Of 2561 respondents (age range 10-35 years; 79.6% ≤ 25 years), 2177 had type 1 diabetes (mean age 21.0 years, 71.8% non-Hispanic white, 11.8% non-Hispanic black, 13.3% Hispanic, 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, 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 on Medicaid/Medicare or without insurance, with lower parental education, and with lower household income had greater odds of experiencing HFI. SNAP participation was 14.1% (95% CI 12.7, 15.5) with higher participation among those with type 2 diabetes compared to type 1 diabetes (34.8% vs. 10.7%; p<0.001).</p> <p>CONCLUSIONS: Almost 1 in 3 YYA with type 2 diabetes and more than 1 in 6 with type 1 diabetes reported HFI in the past year, a significantly higher prevalence than the general U.S. population. </p>

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