Comparison of different obesity indices associated with type 2 diabetes mellitus among different sex and age groups in Nantong, China: a cross-section study

Abstract Background Obesity is associated with type 2 diabetes mellitus (T2DM). However, the obesity index that is most closely related to type 2 diabetes remains controversial. Therefore, the aim of this study was to compare the associations of five anthropometric indices (body mass index [BMI], body adiposity index, waist circumference [WC], waist-to-hip ratio, and waist-to-height ratio [WHtR]) with T2DM among Chinese adults divided into four groups according to sex and age. Methods A total of 4007 adult participants (1669 men and 2338 women) were included in the study. Odds ratios (ORs) and 95% confidence intervals were used with binary logistic regression models to estimate the risk of T2DM for each obesity index. Furthermore, we compared the area under the receiver operating characteristic curve (AUC) of each obesity index for the criterion of T2DM under the influence of risk factors. Results WC had the highest OR (3.211 and 1.452) and AUC (0.783 and 0.614) in both age groups of men. However, WHtR (OR = 2.366, AUC = 0.771) and BMI (OR = 1.596, AUC = 0.647) were the optimal criteria for predicting T2DM among females in the 18–59 and ≥ 60 years age groups, respectively. Conclusions This study suggests that there is a positive association between obesity-related anthropometric indices and T2DM in different sex and age groups. WC appears to be the optimal anthropometric index for predicting T2DM in men. The optimal obesity indices related to T2DM were WHtR and BMI for women aged 18–59 and ≥ 60 years, respectively.

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Comparison of Different Obesity Indices associated with Type 2 Diabetes Mellitus among Different Sex and Age Groups in China

10.21203/rs.3.rs-579184/v1 ◽

2021 ◽

Author(s):

Qiwei Ge ◽

Min Li ◽

Zhengcheng Xu ◽

Zhigang Qi ◽

Huiyan Zheng ◽

...

Keyword(s):

Diabetes Mellitus ◽

Type 2 Diabetes ◽

Type 2 Diabetes Mellitus ◽

Age Groups ◽

Binary Logistic Regression ◽

Positive Association ◽

Anthropometric Indices ◽

Obesity Index ◽

Obesity Indices

Abstract Background: Obesity is associated with type 2 diabetes mellitus (T2DM), but the obesity index most closely related to type 2 diabetes is still controversial. Therefore, the aim of this study was to compare the associations of five anthropometric indices (body mass index (BMI), body adiposity index (BAI), waist circumference (WC), waist-to-hip ratio (WHR), and waist-to-height ratio (WHtR)) with Type 2 diabetes mellitus (T2DM) among Chinese adults divided into four groups according to sex and age.Methods: A total of 4,007 adult participants (1,669 males and 2,338 females) were included. Odds ratios (OR) and 95% confidence intervals were used with binary logistic regression models to estimate the risk of T2DM for each obesity index. Furthermore, we compared the area under the ROC curve (AUC) of each obesity index for the criterion of hypertension under the influence of risk factors. Results: For the males, WC had the highest value of OR (3.211 and 1.452) and AUC (0.783 and 0.614) in both age groups. However, WHtR (OR=2.366, AUC=0.771) and BMI (OR=1.596, AUC=0.647) tended to be the best criteria for T2DM among females in the 18-59 and ≥60 years age groups, respectively.Conclusions: This study suggests that there is a positive association of obesity-related anthropometric indices with T2DM in different sex and age groups. For males, WC appears to be the best anthropometric index for predicting T2DM. For 18-59 and ≥60 age women, the best obesity indices related with T2DM are WHtR and BMI, respectively.

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Comparison of Different Obesity Indices associated with Type 2 Diabetes Mellitus Among Different Sex and Age Groups in China

10.21203/rs.3.rs-154511/v1 ◽

2021 ◽

Author(s):

Qiwei Ge ◽

Min Li ◽

Zhengcheng Xu ◽

Zhigang Qi ◽

Huiyan Zheng ◽

...

Keyword(s):

Diabetes Mellitus ◽

Type 2 Diabetes ◽

Type 2 Diabetes Mellitus ◽

Age Groups ◽

Binary Logistic Regression ◽

Positive Association ◽

Anthropometric Indices ◽

Obesity Index ◽

Obesity Indices

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Relationship between anthropometric indices and insulin resistance in Nigerians with type 2 diabetes mellitus

Endocrine Abstracts ◽

10.1530/endoabs.38.p294 ◽

2015 ◽

Author(s):

Chikezie Onwukwe ◽

Nkiru Chikezie

Keyword(s):

Diabetes Mellitus ◽

Insulin Resistance ◽

Type 2 Diabetes ◽

Type 2 Diabetes Mellitus ◽

Anthropometric Indices

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Association of new obesity indices: visceral adiposity index and body adiposity index, with metabolic syndrome parameters in obese patients with or without type 2 diabetes mellitus

The Egyptian Journal of Internal Medicine ◽

10.1186/s43162-020-00030-z ◽

2021 ◽

Vol 33 (1) ◽

Author(s):

Mahmood Dhahir Al-Mendalawi

Keyword(s):

Diabetes Mellitus ◽

Type 2 Diabetes ◽

Metabolic Syndrome ◽

Type 2 Diabetes Mellitus ◽

Visceral Adiposity Index ◽

Obese Patients ◽

Adiposity Index ◽

Body Adiposity ◽

Obesity Indices

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Lipid Indices vs Anthropometric Indices in Metabolic Syndrome and Type 2 Diabetes Mellitus

Annals of Pathology and Laboratory Medicine ◽

10.21276/apalm.3060 ◽

2021 ◽

Vol 8 (6) ◽

pp. A152-157

Author(s):

Asha Augusthy ◽

Suchanda Sahu ◽

Ashok Kumar Jeppu

Keyword(s):

Diabetes Mellitus ◽

Type 2 Diabetes ◽

Metabolic Syndrome ◽

Type 2 Diabetes Mellitus ◽

Visceral Adiposity ◽

Accumulation Factor ◽

Visceral Adiposity Index ◽

Anthropometric Indices ◽

Adiposity Index

Background: Diabetes mellitus is a metabolic disease known by chronic hyperglycemia which results from defective insulin action and secretion. Metabolic Syndrome consists of a constellation of metabolic abnormalities that confer increased risk of diabetes mellitus. The aim of our study is to find out whether non-invasive, clinically measurable surrogates could be useful in identifying body fat distribution and help predict metabolic syndrome and diabetes risk and to compare the performance of anthropometric indices with lipid indices in identifying metabolic syndrome and diabetes. Methods: 50 individuals with metabolic syndrome ,50 individuals with type 2 diabetes mellitus and 50 controls were selected by purposive sampling technique. For cases and controls history was taken, physical examination was done .Fasting blood sugar, Serum High density lipoprotein and Serum Triglyceride levels were estimated. Body mass index, a body shape index, visceral adiposity index, lipid accumulation factor was calculated. Results: The mean values visceral adiposity index, lipid accumulation factor were significantly increased (p<0.001) in cases compared to controls. Conclusion: Our study concluded that lipid indices visceral adiposity index, lipid accumulation factor is better than anthropometric indices like body mass index, a body shape index in predicting metabolic syndrome and type 2 diabetes mellitus. Anthropometric indices when used should be correlated with metabolic variables and clinical symptoms.

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Estimating the disease burden of Korean type 2 diabetes mellitus patients considering its complications

PLoS ONE ◽

10.1371/journal.pone.0246635 ◽

2021 ◽

Vol 16 (2) ◽

pp. e0246635

Author(s):

Juyoung Kim ◽

Seok-Jun Yoon ◽

Min-Woo Jo

Keyword(s):

Diabetes Mellitus ◽

Type 2 Diabetes ◽

Type 2 Diabetes Mellitus ◽

Markov Model ◽

Burden Of Disease ◽

Age Groups ◽

Years Of Life Lost ◽

Age Group ◽

Disease Study

Background The burden of diabetes is considerable not only globally but also nationally within Korea. The Global Burden of Disease study derived the disability-adjusted life years (DALYs) of diabetes depending on its complications as individual severity using prevalence-based approach from 2017. Conversely, the Korean National Burden of Disease study based on an incidence-based approach does not incorporate the severity of diseases. This study aimed to simulate incidence-based DALYs of type 2 diabetes mellitus (T2DM), given diabetic complications as disease severity using a Markov model. Methods We developed a model with six Markov states, including incident and existing prevalent cases of diabetes and its complications and death. We assumed that diabetes and its complications would not be cured. The cycle length was one year, and the endpoint of the simulation was 100 years. A 5% discount rate was adopted in the analysis. Transition cases were counted by 5-year age groups above 30 years of age. Age- and sex-specific transition probabilities were calculated based on the incident rate. Results The total DALY estimates of T2DM were 5,417 and 3,934 per 100,000 population in men and women, respectively. The years of life lost in men were relatively higher than those in women in most age groups except the 80–84 age group. The distribution of years lived with disability by gender and age group showed a bell shape, peaking in the 55–59 age group in men and 65–69 age group in women. Conclusions The burden of T2DM considering its complications was larger compared to the outcomes from previous studies, with more precise morbid duration using the Markov model.

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Medical service demands of older patients in different age groups in a new model of free Telemedicine

10.21203/rs.3.rs-42072/v1 ◽

2020 ◽

Author(s):

Yu Gong ◽

Jianyuan Zhou

Keyword(s):

Diabetes Mellitus ◽

Type 2 Diabetes ◽

Coronary Heart Disease ◽

Type 2 Diabetes Mellitus ◽

Heart Disease ◽

Older Patients ◽

Medical Service ◽

Age Groups ◽

New Model

Abstract Background Medical service for the older patients is a worldwide challenge for public health system. Telemedicine can provide convenient and effective medical service for older patients. But the existing telemedicine models rely upon a direct communication between a doctor and a patient via the Internet but the doctor would be unable to give the patient a direct physical examination, it may lead to diagnostic errors. A new model of telemedicine jointly performed by general practitioners in community health centers and specialists in a university teaching hospital has been established. It is supervised by the government health department and is free for older patients. However, medical service demands of older patients in different age groups applying the new telemedicine are not well characterized. This study is to analyze medical service demands of older patients in different age groups applying the new telemedicine. Methods 472 older patients (aged ≥ 60) were enrolled and were divided into the young older group (aged 60 to 74), the old older group (aged 75 to 89) and the very old group (aged ≥ 90) according to the age stratification for older people defined by World Health Organization. Proportion of the top 10 diseases of older patients of different age groups was analyzed. Results Coronary heart disease and type 2 diabetes mellitus were identified as the top two diseases in the older patients and the young older patients as well as the old older patients applying the new telemedicine. Conclusions The new telemedicine model can provide effective free medical services to older patients. Different medical service demands were identified in different age groups of older patients. Coronary heart disease and type 2 diabetes mellitus were the main diseases of the older patients and young older patients as well as the old older patients applying the new telemedicine. Results of this study will provide basis for the health administrative departments to formulate health policies for older patients. Familiar with the main diseases in different age groups of older patients may provide better medical services to older patients.

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The relationship between metabolic factors and anthropometric indices with periodontal status in type 2 diabetes mellitus patients with chronic periodontitis

Obesity Medicine ◽

10.1016/j.obmed.2019.100138 ◽

2019 ◽

Vol 16 ◽

pp. 100138 ◽

Cited By ~ 2

Author(s):

Hadi Bazyar ◽

Azim Adibmanesh ◽

Ahmad Zare Javid ◽

Leila Maghsoumi-Norouzabad ◽

Ehsan Gravand ◽

...

Keyword(s):

Diabetes Mellitus ◽

Type 2 Diabetes ◽

Type 2 Diabetes Mellitus ◽

Chronic Periodontitis ◽

Metabolic Factors ◽

Anthropometric Indices ◽

Periodontal Status ◽

The Relationship

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The Performance of Different Artificial Intelligence Models in Predicting Breast Cancer among Individuals Having Type 2 Diabetes Mellitus

Cancers ◽

10.3390/cancers11111751 ◽

2019 ◽

Vol 11 (11) ◽

pp. 1751 ◽

Cited By ~ 1

Author(s):

Meng-Hsuen Hsieh ◽

Li-Min Sun ◽

Cheng-Li Lin ◽

Meng-Ju Hsieh ◽

Chung Hsu ◽

...

Keyword(s):

Breast Cancer ◽

Diabetes Mellitus ◽

Type 2 Diabetes ◽

Type 2 Diabetes Mellitus ◽

Characteristic Curve ◽

Small Population ◽

Research Database ◽

Artificial Intelligence Models ◽

Artificial Neural Network Ann

Objective: Early reports indicate that individuals with type 2 diabetes mellitus (T2DM) may have a greater incidence of breast malignancy than patients without T2DM. The aim of this study was to investigate the effectiveness of three different models for predicting risk of breast cancer in patients with T2DM of different characteristics. Study design and methodology: From 2000 to 2012, data on 636,111 newly diagnosed female T2DM patients were available in the Taiwan’s National Health Insurance Research Database. By applying their data, a risk prediction model of breast cancer in patients with T2DM was created. We also collected data on potential predictors of breast cancer so that adjustments for their effect could be made in the analysis. Synthetic Minority Oversampling Technology (SMOTE) was utilized to increase data for small population samples. Each datum was randomly assigned based on a ratio of about 39:1 into the training and test sets. Logistic Regression (LR), Artificial Neural Network (ANN) and Random Forest (RF) models were determined using recall, accuracy, F1 score and area under the receiver operating characteristic curve (AUC). Results: The AUC of the LR (0.834), ANN (0.865), and RF (0.959) models were found. The largest AUC among the three models was seen in the RF model. Conclusions: Although the LR, ANN, and RF models all showed high accuracy predicting the risk of breast cancer in Taiwanese with T2DM, the RF model performed best.

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