Prevalence and correlates of diabetes distress, perceived stress and depressive symptoms among adults with early‐onset Type 2 diabetes: cross‐sectional survey results from the Danish DD2 study

2019 ◽  
Author(s):  
A. Bo ◽  
F. Pouwer ◽  
L. Juul ◽  
S. K. Nicolaisen ◽  
H. T. Maindal
Keyword(s):  
Type 2 Diabetes ◽  
Depressive Symptoms ◽  
Perceived Stress ◽  
Early Onset ◽  
Diabetes Distress ◽  
Cross Sectional Survey ◽  
Cross Sectional ◽  
Onset Type ◽  
Survey Results

scholarly journals Early-onset type 2 diabetes in a Mexican survey: results from the National Health and Nutrition Survey 2006

2010 ◽  
Vol 52 ◽  
pp. S27-S35 ◽  
Author(s):  
Aída Jiménez-Corona ◽  
Rosalba Rojas ◽  
Francisco J Gómez-Pérez ◽  
Carlos A Aguilar-Salinas
Keyword(s):  
Type 2 Diabetes ◽  
National Health ◽  
Early Onset ◽  
Nutrition Survey ◽  
Onset Type ◽  
Health And Nutrition ◽  
Survey Results

scholarly journals Diabetes Distress in Young Adults with Type 2 Diabetes: A Cross-Sectional Survey in China

2020 ◽  
Vol 2020 ◽  
pp. 1-6
Author(s):  
Yanfen Hu ◽  
Lingxia Li ◽  
Jun Zhang
Keyword(s):  
Type 2 Diabetes ◽  
Young Adults ◽  
Regression Analysis ◽  
Diabetes Complications ◽  
Self Management ◽  
Diabetes Distress ◽  
Cross Sectional Survey ◽  
Cross Sectional ◽  
Main Factors

Background. Diabetes distress is a negative emotion related to diabetes management, which can compromise self-care and management of diabetes. However, few studies on diabetes distress have focused on young adults with type 2 diabetes in China. Methods. A cross-sectional survey was conducted. Using a convenient sampling method, 98 young adults with type 2 diabetes who were admitted to our hospital from June 2017 to July 2018 were selected as research subjects. They were investigated using a basic demographic questionnaire, Diabetes Distress Scale, Summary of Diabetes Self-Care Activities Measure, and Audit of Disease Knowledge. Pearson’s correlation analysis and regression analysis were used to analyze the influencing factors of diabetic distress. Results. Among participants, 90.82% suffered from diabetes distress with an average score of 3.01±0.58. Regimen-related, emotional burden-related, and interpersonal-related distress were the most frequently reported as severe. The results of the single-factor analysis showed that gender (P=0.019), age (P=0.003), occupation (P=0.022), smoking (P<0.001), and diabetes complications (P=0.001) were the main factors affecting diabetes distress. The correlation analysis showed that diabetes distress was negatively correlated with the level of diabetic self-management (P<0.001, r=−0.377) but not with the level of diabetes knowledge (P=0.052, r=−0.197). The results of a multiple regression analysis showed that self-management level (P=0.001, 95% CI: -0.039-0.011), age (P=0.002, 95% CI: -0.463-0.104), smoking (P=0.018, 95% CI: -0.504-0.048), and complications (P=0.009, 95% CI: -0.517-0.076) accounted for 35.42% of the total variation in diabetes distress. Conclusion. Young adults with type 2 diabetes reported severe diabetes distress. Age, smoking, and diabetes complications were the main factors influencing diabetes distress in young adults with type 2 diabetes. Results of the present study are fundamental in selecting targeted measures for alleviating diabetes distress and thus improving the quality of life in these patients.

Vitamin D concentrations from neonatal dried blood spots and the risk of early-onset type 2 diabetes in the Danish D-tect case-cohort study

Diabetologia ◽  
2021 ◽  
Author(s):  
Amélie Keller ◽  
Fanney Thorsteinsdottir ◽  
Maria Stougaard ◽  
Isabel Cardoso ◽  
Peder Frederiksen ◽  
...  
Keyword(s):  
Type 2 Diabetes ◽  
Vitamin D ◽  
Cohort Study ◽  
Early Onset ◽  
Dried Blood Spots ◽  
Onset Type ◽  
Blood Spots

scholarly journals Predictors of frailty among Chinese community-dwelling older adults with type 2 diabetes: a cross-sectional survey

BMJ Open ◽  
2021 ◽  
Vol 11 (3) ◽  
pp. e041578
Author(s):  
Linglin Kong ◽  
Huimin Zhao ◽  
Junyao Fan ◽  
Quan Wang ◽  
Jie Li ◽  
...  
Keyword(s):  
Type 2 Diabetes ◽  
Older Adults ◽  
Depressive Symptoms ◽  
Community Health ◽  
Community Dwelling ◽  
Central China ◽  
Chinese Community ◽  
Cross Sectional ◽  
Community Dwelling Older Adults

ObjectivesTo assess the prevalence of frailty and identify predictors of frailty among Chinese community-dwelling older adults with type 2 diabetes.DesignA cross-sectional design.SettingTwo community health centres in central China.Participants291 community-dwelling older adults aged ≥65 years with type 2 diabetes.Main outcome measuresData were collected via face-to-face interviews, anthropometric measurements, laboratory tests and community health files. The main outcome measure was frailty, as assessed by the frailty phenotype criteria. The multivariate logistic regression model was used to identify the predictors of frailty.ResultsThe prevalence of prefrailty and frailty were 51.5% and 19.2%, respectively. The significant predictors of frailty included alcohol drinking (ex-drinker) (OR 4.461, 95% CI 1.079 to 18.438), glycated haemoglobin (OR 1.434, 95% CI 1.045 to 1.968), nutritional status (malnutrition risk/malnutrition) (OR 8.062, 95% CI 2.470 to 26.317), depressive symptoms (OR 1.438, 95% CI 1.166 to 1.773) and exercise behaviour (OR 0.796, 95% CI 0.716 to 0.884).ConclusionsA high prevalence of frailty was found among older adults with type 2 diabetes in the Chinese community. Frailty identification and multifaceted interventions should be developed for this population, taking into consideration proper glycaemic control, nutritional instruction, depressive symptoms improvement and enhancement of self-care behaviours.

scholarly journals Missense mutations in theTGM2 gene encoding transglutaminase 2 are found in patients with early-onset type 2 diabetes

2007 ◽  
Vol 28 (11) ◽  
pp. 1150-1150 ◽  
Author(s):  
O. Porzio ◽  
O. Massa ◽  
V. Cunsolo ◽  
C. Colombo ◽  
M. Malaponti ◽  
...  
Keyword(s):  
Type 2 Diabetes ◽  
Early Onset ◽  
Transglutaminase 2 ◽  
Missense Mutations ◽  
Gene Encoding ◽  
Onset Type
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