Dynamics of diabetes and obesity: Epidemiological perspective

Biochimica et Biophysica Acta (BBA) - Molecular Basis of Disease, Journal Year: 2017, Volume and Issue: 1863(5), P. 1026 - 1036

Published: Jan. 25, 2017

Language: Английский

---

Building Risk Prediction Models for Type 2 Diabetes Using Machine Learning Techniques

Preventing Chronic Disease, Journal Year: 2019, Volume and Issue: 16

Published: Sept. 19, 2019

As one of the most prevalent chronic diseases in United States, diabetes, especially type 2 affects health millions people and puts an enormous financial burden on US economy. We aimed to develop predictive models identify risk factors for which could help facilitate early diagnosis intervention also reduce medical costs.We analyzed cross-sectional data 138,146 participants, including 20,467 with from 2014 Behavioral Risk Factor Surveillance System. built several machine learning predicting support vector machine, decision tree, logistic regression, random forest, neural network, Gaussian Naive Bayes classifiers. used univariable multivariable weighted regression investigate associations potential diabetes.All diabetes achieved a high area under curve (AUC), ranging 0.7182 0.7949. Although network model had highest accuracy (82.4%), specificity (90.2%), AUC (0.7949), tree sensitivity (51.6%) diabetes. found that who slept 9 or more hours per day (adjusted odds ratio [aOR] = 1.13, 95% confidence interval [CI], 1.03-1.25) checkup frequency less than 1 year (aOR 2.31, CI, 1.86-2.85) higher diabetes.Of 8 models, gave best performance value; however, is preferred initial screening because it and, therefore, detection rate. confirmed previously reported identified sleeping time as new related

Language: Английский

---

Prevalence of Prediabetes, Diabetes, and Its Associated Risk Factors among Males in Saudi Arabia: A Population-Based Survey

Journal of Diabetes Research, Journal Year: 2018, Volume and Issue: 2018, P. 1 - 12

Published: Jan. 1, 2018

Objectives . The study aims at determining the prevalence of prediabetes and diabetes ascertaining some concomitant risk factors among males in Saudi Arabia. Methods A population-based cross-sectional including 381 adult from different institutions was recruited. Odds ratios for were calculated using log-binomial multinomial logistic regression, STATA version 12. Results participants included diabetic with a median age 45 years, average body mass index 25 ± 40 kg/m 2 , whereas waist circumferences ranged 66 to 180 cm male population. In addition, 27.82% had normal BMI, 32.28% overweight, 36.22% obese. Around 36% higher circumference, that is, >102 cm. Age, marital status, educational attainment statistically significant predictors diabetes. Conclusion This found 9.2% 27.6%, respectively, Al-Kharj increase include older age, obesity being married, smoker, having civilian job less education. All these except smoking status type. order evaluate causal relationship factors, prospective studies are required future.

Language: Английский

---

Prevalence and factors associated with prediabetes and diabetes in fishing communities in penang, Malaysia: A cross-sectional study

PLoS ONE, Journal Year: 2020, Volume and Issue: 15(2), P. e0228570 - e0228570

Published: Feb. 10, 2020

Background Diabetes is a metabolic disorder, characterized by hyperglycemic state of the body. A silent killer, which can take lives victims if undiagnosed at earliest stage. Prediabetes has become an important health concern across countries due to its huge potential for development diabetes and other complications. The objectives this study were determine prevalence prediabetes associated factors among rural fishing communities in Penang, Malaysia. Methods cross-sectional was conducted Southwest District Malaysia from August November 2017. Blood sample (finger prick test) physical examination performed on 168 participants consented study. Pre-validated Malay versions International Physical Activity 7 (IPAQ-7) Perceived Stress Scale (PSS) questionnaires used assess level activity stress levels participants. Multinomial logistic regression models fitted identify with diabetes. Results 19.6% (95% CI: 14.3, 26.4) 10.12% 6.4, 15.7) respectively. median (interquartile range) MET-minutes per week those (1071.0 (2120.0)) (1314.0 (1710.0)) generally lower as compared non-diabetes. Majority reported moderate (57.3%) PSS system. Abdominal obesity, family history being hypertensive significant diabetes; while older age, bigger waist circumference self-perceived poor routine diet prediabetes. Conclusions screening population gives opportunity implement lifestyle interventions possible, could prevent identification diabetic individuals provides conduct promotion education ensure good control hence reduce risks

Language: Английский

---

Incidence Rate of Prediabetes Progression to Diabetes: Modeling an Optimum Target Group for Intervention

Population Health Management, Journal Year: 2016, Volume and Issue: 20(3), P. 216 - 223

Published: Sept. 30, 2016

Thirty-seven percent of US adults have prediabetes. Various interventions can delay diabetes progression; however, the optimum target group for risk reduction is uncertain. This study estimated rate progression to at 1 and 5 years among a cohort patients from 3 primary care clinics modeled potential magnitude in incidence an intervention program specific subgroups. Records 106,821 empaneled 2005 were reviewed. Generalized population attributable (PAR) statistics calculated estimate impact reducing fasting blood glucose on progression. Multiple effects (varying levels along with multiple adherence rates) examined those baseline 110 119 mg/dL ≥120 mg/dL. Ten (n = 10,796) met criteria The 1- 5-year was 38.6 40.24 per 1000 person-years, respectively. Age obesity independent predictors increased rate. generalized PAR 10-point 110–119 subgroup 25% 7.6%. similar level only 3.0%. Rate over time associated factors. Greater within be achieved when successful Modeling prevention offers novel useful guide planning allocating resources health management.

Language: Английский

---

Associations of lipid profiles with insulin resistance and β cell function in adults with normal glucose tolerance and different categories of impaired glucose regulation

PLoS ONE, Journal Year: 2017, Volume and Issue: 12(2), P. e0172221 - e0172221

Published: Feb. 15, 2017

To investigate the associations of dyslipidemia with insulin resistance and β cell function in individuals normal glucose tolerance (NGT) different categories impaired regulation (IGR).544 subjects (365 and/or IGR 179 lipid tolerance) were enrolled study. All underwent oral test (OGTT). HOMA-IR was used to evaluate sensitivity. Disposition index (DI) function. Multiple linear regression analysis performed assess correlations among profiles, function.Among NGT, those had higher level but lower DI. While IGR, CGI significantly decreased No obvious differences or found IFG IGT without dyslipidemia. TG HDL-C correlated (β = 0.79, p <0.001; -0.38, 0.027, respectively, compared low groups). Moreover, TC negatively DI -2.17, 0.013; -2.01, 0.034 groups) after adjusting for confounding parameters.Dyslipidemia induces response NGT. Furthermore, diminishes CGI. resistance, TG, non-diabetic individuals.

Language: Английский

---

Prevalence of Pre-Diabetes and Its Associated Risk Factors in Rural Areas of Ningbo, China

International Journal of Environmental Research and Public Health, Journal Year: 2016, Volume and Issue: 13(8), P. 808 - 808

Published: Aug. 10, 2016

The aims of the study were to investigate prevalence pre-diabetes and explore its associated risk factors in rural areas Ningbo, China.A cross-sectional survey was conducted with 4583 adult residents China between March May 2013. used a multi-stage, stratified, cluster sampling method. Data collected included demographics medical history, anthropometric measurements, blood pressure, lipid, plasma glucose. After at least 10 h overnight fasting, participants underwent an oral glucose tolerance test (OGTT) identify pre-diabetes. Univariate multivariate logistic regression analyses evaluate for pre-diabetes, estimate effect interaction factors.There 1307 having (28.52%) age-standardized 30.53%. Multivariate results showed that overweight/obesity, hypertension, higher triglycerides developing There positive interactions overweight/obesity triglycerides, also hypertension on multiplicative scale, suggesting they synergistically influenced development pre-diabetes.The Ningbo had high Overweight obesity, elevated major factors. is need early intervention preventing

Language: Английский

---

Sex and age differences in prevalence and risk factors for prediabetes in Mexican-Americans

Diabetes Research and Clinical Practice, Journal Year: 2019, Volume and Issue: 159, P. 107950 - 107950

Published: Dec. 2, 2019

Language: Английский

---

Prevalence and Risk Factors of Type 2 Diabetes and Prediabetes Among 53,288 Middle-Aged and Elderly Adults in China: A Cross-Sectional Study

Diabetes Metabolic Syndrome and Obesity, Journal Year: 2021, Volume and Issue: Volume 14, P. 1975 - 1985

Published: May 1, 2021

Diabetes is a metabolic disorder that causes heavy burden on healthcare systems worldwide. The aim of this study was to determine the prevalence type 2 diabetes and prediabetes its associated factors among eight communities in Nanchong, China.This an observational cross-sectional conducted throughout China. participants were 53,288 individuals aged 45 years or older. participants' characteristics, comorbidities, health behaviors, family history, dietary intake assessed. Multinomial logistic regression models fitted identify with prediabetes.The 13.9% (95% confidence interval [CI], 13.6-14.2) 3.1% CI, 2.9-3.2) population, respectively. After adjusting for other risk factors, advanced age, overweight, obesity, abdominal smoking, history diabetes, Chinese cooking vegetable increased population rising compared data from past. identified will aid identification at high-risk implementation effective promotion programs campaigns.ChiCTR-HOC-17013200.

Language: Английский

---

Predictors of county-level diabetes-related mortality risks in Florida, USA: a retrospective ecological study

PeerJ, Journal Year: 2025, Volume and Issue: 13, P. e18537 - e18537

Published: Jan. 16, 2025

Diabetes is an increasingly important public health problem due to its socioeconomic impact, high morbidity, and mortality. Although there evidence of increasing diabetes-related deaths over the last ten years, little known about population level predictors mortality risks (DRMR) in Florida. Identifying these for guiding control programs geared at reducing diabetes burden improving health. Therefore, objective this study was identify geographic disparities county-level DRMR The 2019 data state Florida were obtained from Department Health. 10th International Classification Disease codes E10-E14 used which then aggregated county-level. County-level computed presented as number per 100,000 persons. Geographic distribution displayed choropleth maps ordinary least squares (OLS) regression model DRMR. There a total 6,078 during time period. ranged 9.6 75.6 High observed northern, central, southcentral parts state. Relatively higher identified rural counties compared their urban counterparts. Significantly with percentages that were: 65 year older (p < 0.001), current smokers = 0.032), insufficiently physically active 0.036). Additionally, percentage households without vehicles 0.022) 0.001) significant exist Florida, being findings are useful professionals better target intervention efforts.

Language: Английский

---