scholarly journals Sedentary lifestyle and body composition in type 2 diabetes

2022 ◽  
Vol 14 (1) ◽  
Author(s):  
Dan-dan Li ◽  
Yang Yang ◽  
Zi-yi Gao ◽  
Li-hua Zhao ◽  
Xue Yang ◽  
...  
Keyword(s):  
Type 2 Diabetes ◽  
Skeletal Muscle ◽  
Body Composition ◽  
Lumbar Spine ◽  
Sedentary Time ◽  
Sedentary Lifestyle ◽  
Body Fat Percentage ◽  
Fat Percentage ◽  
Appendicular Skeletal Muscle

Abstract Background Body composition alterations may participate in the pathophysiological processes of type 2 diabetes (T2D). A sedentary lifestyle may be responsible for alterations of body composition and adverse consequences, but on which body composition of patients with T2D and to what extent the sedentary lifestyle has an effect have been poorly investigated. Methods We recruited 402 patients with T2D for this cross-sectional study. All patients received questionnaires to evaluate sedentary time and were further divided into three subgroups: low sedentary time (LST, < 4 h, n = 109), middle sedentary time (MST, 4–8 h, n = 129) and high sedentary time (HST, > 8 h, n = 164). Each patient underwent a dual energy X-ray absorptiometry (DXA) scan to detect body composition, which included body fat percentage (B-FAT), trunk fat percentage (T-FAT), appendicular skeletal muscle index (ASMI), lumbar spine bone mineral density (BMD) (LS-BMD), femoral neck BMD (FN-BMD), hip BMD (H-BMD) and total BMD (T-BMD). Other relevant clinical data were also collected. Results With increasing sedentary time (from the LST to HST group), B-FAT and T-FAT were notably increased, while ASMI, LS-BMD, FN-BMD, H-BMD and T-BMD were decreased (p for trend < 0.01). After adjustment for other relevant clinical factors and with the LST group as the reference, the adjusted mean changes [B (95% CI)] in B-FAT, T-FAT, ASMI, LS-BMD, FN-BMD, H-BMD and T-BMD in the HST group were 2.011(1.014 to 3.008)%, 1.951(0.705 to 3.197)%, − 0.377(− 0.531 to − 0.223) kg/m2, − 0.083(− 0.124 to − 0.042) g/cm2, − 0.051(− 0.079 to − 0.024) g/cm2, − 0.059(− 0.087 to − 0.031) g/cm2 and − 0.060(− 0.088 to − 0.033) g/cm2, p < 0.01, respectively. Conclusions A sedentary lifestyle may independently account for increases in trunk and body fat percentage and decreases in appendicular skeletal muscle mass and BMD of the lumbar spine, femoral neck, hip and total body in patients with T2D.

scholarly journals Differences in Body Composition Convey a Similar Risk of Type 2 Diabetes Among Different Ethnic Groups With Disparate Cardiometabolic Risk—The HELIUS Study

2021 ◽  
Author(s):  
Marleen Zethof ◽  
Charlotte M. Mosterd ◽  
Didier Collard ◽  
Henrike Galenkamp ◽  
Charles Agyemang ◽  
...  
Keyword(s):  
Type 2 Diabetes ◽  
Body Composition ◽  
Ethnic Groups ◽  
South Asian ◽  
Cardiometabolic Risk ◽  
Body Fat Percentage ◽  
Fat Percentage ◽  
C Statistic ◽  
Helius Study

<b>Objective</b>: Studies have shown a disparate association between body composition and the risk of type 2 diabetes. We assessed whether associations between differences in body composition and type 2 diabetes vary among ethnic groups with disparate cardiometabolic risk. <p><b>Research Design and Methods: </b>We used data from the HELIUS study, including individuals aged 18-70 of<b> </b>African Surinamese (n=3997), South-Asian Surinamese (n=2956), Turkish (n=3546), Moroccan (n=3850), Ghanaian (n=2271) and Dutch (n=4452) origin living in Amsterdam. Type 2 diabetes was defined using the World Health Organization criteria. Logistic regression was used to assess the relation between body composition and type 2 diabetes. Waist-hip ratio, waist circumference, BMI and body fat percentage by bio-electrical impedance were used to estimate body composition.</p> <p><b>Results: </b>Per unit change in BMI only Ghanaian [OR 0.94 (95% CI 0.89-0.99)] and Moroccan [0.94 (0.89-0.99)] women had a smaller increase in type 2 diabetes per unit change in BMI compared to the Dutch population, while OR for body fat percentage were 0.94 (0.89-1.00) for Ghanaian, 0.93 (0.88-0.99) for Moroccan and 0.95 (0.90-1.00) for South-Asian Surinamese women. There was no interaction between WHR and ethnicity on the risk of type 2 diabetes, and there were no differences in men. WHR had the highest precision in predicting type 2 diabetes in both men (c-statistic=0.78) and women (c-statistic=0.81). </p> <b>Conclusions: </b>The<b> </b>association between differences in body composition and type 2 diabetes is roughly the same in all ethnic groups. WHR seems the most reliable and consistent predictor of type 2 diabetes regardless of ethnic background.<b> </b>

scholarly journals Differences in Body Composition Convey a Similar Risk of Type 2 Diabetes Among Different Ethnic Groups With Disparate Cardiometabolic Risk—The HELIUS Study

2021 ◽  
Author(s):  
Marleen Zethof ◽  
Charlotte M. Mosterd ◽  
Didier Collard ◽  
Henrike Galenkamp ◽  
Charles Agyemang ◽  
...  
Keyword(s):  
Type 2 Diabetes ◽  
Body Composition ◽  
Ethnic Groups ◽  
South Asian ◽  
Cardiometabolic Risk ◽  
Body Fat Percentage ◽  
Fat Percentage ◽  
C Statistic ◽  
Helius Study

<b>Objective</b>: Studies have shown a disparate association between body composition and the risk of type 2 diabetes. We assessed whether associations between differences in body composition and type 2 diabetes vary among ethnic groups with disparate cardiometabolic risk. <p><b>Research Design and Methods: </b>We used data from the HELIUS study, including individuals aged 18-70 of<b> </b>African Surinamese (n=3997), South-Asian Surinamese (n=2956), Turkish (n=3546), Moroccan (n=3850), Ghanaian (n=2271) and Dutch (n=4452) origin living in Amsterdam. Type 2 diabetes was defined using the World Health Organization criteria. Logistic regression was used to assess the relation between body composition and type 2 diabetes. Waist-hip ratio, waist circumference, BMI and body fat percentage by bio-electrical impedance were used to estimate body composition.</p> <p><b>Results: </b>Per unit change in BMI only Ghanaian [OR 0.94 (95% CI 0.89-0.99)] and Moroccan [0.94 (0.89-0.99)] women had a smaller increase in type 2 diabetes per unit change in BMI compared to the Dutch population, while OR for body fat percentage were 0.94 (0.89-1.00) for Ghanaian, 0.93 (0.88-0.99) for Moroccan and 0.95 (0.90-1.00) for South-Asian Surinamese women. There was no interaction between WHR and ethnicity on the risk of type 2 diabetes, and there were no differences in men. WHR had the highest precision in predicting type 2 diabetes in both men (c-statistic=0.78) and women (c-statistic=0.81). </p> <b>Conclusions: </b>The<b> </b>association between differences in body composition and type 2 diabetes is roughly the same in all ethnic groups. WHR seems the most reliable and consistent predictor of type 2 diabetes regardless of ethnic background.<b> </b>

Body Fat Percentage Rather than Body Mass Index Related to the High Occurrence of Type 2 Diabetes

2020 ◽  
Vol 51 (6) ◽  
pp. 564-571 ◽  
Author(s):  
Jorge Escobedo-de la Peña ◽  
Jorge Alejandro Ramírez-Hernández ◽  
María Teresa Fernández-Ramos ◽  
Evangelina González-Figueroa ◽  
Beatriz Champagne
Keyword(s):  
Type 2 Diabetes ◽  
Body Mass Index ◽  
Body Mass ◽  
Body Fat ◽  
Body Fat Percentage ◽  
Fat Percentage ◽  
High Occurrence

scholarly journals Sarcopenia and Appendicular Muscle Mass as Predictors of Impaired Fasting Glucose/Type 2 Diabetes in Elderly Women

Nutrients ◽  
2021 ◽  
Vol 13 (6) ◽  
pp. 1909
Author(s):  
Carola Buscemi ◽  
Yvelise Ferro ◽  
Roberta Pujia ◽  
Elisa Mazza ◽  
Giada Boragina ◽  
...  
Keyword(s):  
Type 2 Diabetes ◽  
Skeletal Muscle ◽  
Muscle Mass ◽  
Skeletal Muscle Mass ◽  
Elderly Women ◽  
Fasting Glucose ◽  
University Hospital ◽  
Appendicular Skeletal Muscle ◽  
Appendicular Skeletal Muscle Mass

Elderly women exhibit a high risk of type 2 diabetes (T2D), but no definitive data exist about the possible role of postmenopausal increases in visceral adiposity, the loss of lean body mass, or decreases in the sum of the lean mass of arms and legs (appendicular skeletal muscle mass (ASMM)). This retrospective, longitudinal study investigated whether body composition (bioelectrical impedance analysis) predicted the development of impaired fasting glucose (IFG) or T2D in a cohort of 159 elderly women (age: 71 ± 5 years, follow-up: 94 months) from southern Italy (Clinical Nutrition and Geriatric Units of the “Mater Domini” University Hospital in Catanzaro, Calabria region, and the “P. Giaccone ”University Hospital in Palermo, Sicily region). Sarcopenia was defined in a subgroup of 128 women according to the EWGSOP criteria as the presence of low muscle strength (handgrip strength <16 kg) plus low muscle mass (reported as appendicular skeletal muscle mass <15 kg). Participants with a low ASMM had a higher IFG/T2D incidence than those with a normal ASMM (17% vs. 6%, p-adjusted = 0.044); this finding was independent of BMI, fat mass, waist circumference, and habitual fat intake (OR = 3.81, p = 0.034). A higher incidence of IFG/T2D was observed in the subgroup with sarcopenia than those without sarcopenia (33% vs. 7%, p-adjusted = 0.005) independent of BMI and fat mass (OR = 6.75, p = 0.007). In conclusion, this study demonstrates that elderly women with low ASMM had a higher probability of developing IFG/T2D. Further studies are needed to confirm these results in men and in other age groups.

scholarly journals Trends in HbA1c Change Among Youth Referred to a Pediatric Type 2 Diabetes Prevention Clinic

2021 ◽  
Vol 5 (Supplement_1) ◽  
pp. A663-A663
Author(s):  
Emily Paprocki ◽  
Yun Yan ◽  
Brian R Lee ◽  
Mitchell Barnes ◽  
Francesco De Luca ◽  
...  
Keyword(s):  
Type 2 Diabetes ◽  
Body Fat ◽  
Body Fat Percentage ◽  
Initial Visit ◽  
Pediatric Endocrinology ◽  
Fat Percentage ◽  
Type 2 Diabetes Prevention ◽  
Race Ethnicity

Abstract Background: Pediatric type 2 diabetes (T2D) has increased in prevalence as childhood obesity rates climb. More youth are being referred to pediatric endocrinology due to the concern for developing T2D, yet prediction of which children will progress to overt T2D is challenging. We describe a single center experience with pediatric prediabetes referrals and trends in HbA1c change. Methods: Retrospective review of new patients seen at a Type 2 Diabetes Prevention (T2DP) Clinic July 2015 - December 2019. All children referred to T2DP Clinic have an elevated BMI and findings of insulin resistance/prediabetes/early T2D. They are evaluated by pediatric endocrinology providers and dieticians at each visit. The outcome of interest was categorical HbA1c change between patients’ initial and most recent T2DP Clinic visit. Only HbA1c measurements conducted at the study site were included to address inconsistencies in lab assays. HbA1c at the initial visit was categorized into 3 groups: 1) &lt; 5.7%; 2) 5.7 to &lt;6.5%; 3) 6.5% to &lt;8.5%. Final HbA1c was categorized similarly with the option to progress to a 4th HbA1c group of ≥8.5%. Patients were categorized as progressors, regressors, or stable depending on change in group (e.g., group 1 --&gt; group 2) between initial and most recent HbA1c. Comparisons between groups were made using ANOVA and Fisher’s exact tests. Results: Among 297 patients seen for an initial visit, mean BMI z-score was 2.3 and body fat percentage was 44%. High blood pressure occurred in 47%, high ALT in 24%, low HDL in 14%. Prevalence of initial HbA1c &lt; 5.7%, 5.7 to &lt; 6.5%, and 6.5% to &lt; 8.5% was 46%, 42%, and 12%, respectively. One-third (31%) were prescribed metformin at their initial visit. Only 63 patients (21%) had 2 or more visits in the T2DP Clinic with study site HbA1c data available. Of those 63 patients, mean age at initial visit was 12.5 years, BMI z-score 2.0, and body fat 46%. Most patients were female (68%) with public insurance (70%). Race/ethnicity was 35% black, 29% white, 30% Hispanic. Mean time between initial and most recent HbA1c was 11.9 months. Assessment of categorical HbA1c change showed 14% of patients with progression (n=9), 65% stable (n=41), and 21% with regression (n=13). Female sex, ALT elevation, HbA1c, fasting glucose were found to be statistically different between the groups at baseline (p &lt; 0.05). Age, race/ethnicity, BMI, body fat percentage, elevated blood pressure, lipid profile, 120-minute glucose on OGTT, and metformin use were not different between the groups. Conclusions. Only 14% of children who presented for follow up in our T2DP clinic demonstrated progression in HbA1c. Risk factors for those who progress include female sex and ALT elevation. Further development of predictive models to identify this high-risk population who will progress is necessary. Retaining consistent follow up in pediatric prediabetes clinics presents a challenge.

scholarly journals Network Mendelian randomization study: exploring the causal pathway from insomnia to type 2 diabetes

2022 ◽  
Vol 10 (1) ◽  
pp. e002510
Author(s):  
Wen Xiuyun ◽  
Lin Jiating ◽  
Xie Minjun ◽  
Li Weidong ◽  
Wu Qian ◽  
...  
Keyword(s):  
Type 2 Diabetes ◽  
Body Fat ◽  
Mendelian Randomization ◽  
Body Fat Percentage ◽  
Causal Association ◽  
Fat Percentage ◽  
Waist To Hip Ratio ◽  
Increased Risk ◽  
Causal Pathway

IntroductionInsomnia is a novel pathogen for type 2 diabetes mellitus (T2DM). However, mechanisms linking insomnia and T2DM are poorly understood. In this study, we apply a network Mendelian randomization (MR) framework to determine the causal association between insomnia and T2DM and identify the potential mediators, including overweight (body mass index (BMI), waist-to-hip ratio, and body fat percentage) and glycometabolism (HbA1c, fasting blood glucose, and fasting blood insulin).Research design and methodsWe use the MR framework to detect effect estimates of the insomnia–T2DM, insomnia–mediator, and mediator–T2DM associations. A mediator between insomnia and T2DM is established if MR studies in all 3 steps prove causal associations.ResultsIn the Inverse variance weighted method, the results show that insomnia will increase the T2DM risk (OR 1.142; 95% CI 1.072 to 1.216; p=0.000), without heterogeneity nor horizontal pleiotropy, strongly suggesting that genetically predicted insomnia has a causal association with T2DM. Besides, our MR analysis provides strong evidence that insomnia is causally associated with BMI and body fat percentage. There is also suggestive evidence of an association between insomnia and the waist-to-hip ratio. At the same time, our results indicate that insomnia is not causally associated with glycometabolism. Higher BMI, waist-to-hip ratio, and body fat percentage levels are strongly associated with increased risk of T2DM.ConclusionsGenetically predicted insomnia has a causal association with T2DM. Being overweight (especially BMI and body fat percentage) mediates the causal pathway from insomnia to T2DM.

scholarly journals Body fat predicts exercise capacity in persons with Type 2 Diabetes Mellitus: A machine learning approach

PLoS ONE ◽  
2021 ◽  
Vol 16 (3) ◽  
pp. e0248039
Author(s):  
Tanmay Nath ◽  
Rexford S. Ahima ◽  
Prasanna Santhanam
Keyword(s):  
Diabetes Mellitus ◽  
Machine Learning ◽  
Type 2 Diabetes ◽  
Body Composition ◽  
Exercise Capacity ◽  
Body Fat ◽  
Baseline Data ◽  
Fat Percentage ◽  
Maximum Exercise

Diabetes mellitus is associated with increased cardiovascular disease (CVD) related morbidity, mortality and death. Exercise capacity in persons with type 2 diabetes has been shown to be predictive of cardiovascular events. In this study, we used the data from the prospective randomized LOOK AHEAD study and used machine learning algorithms to help predict exercise capacity (measured in Mets) from the baseline data that included cardiovascular history, medications, blood pressure, demographic information, anthropometric and Dual-energy X-Ray Absorptiometry (DXA) measured body composition metrics. We excluded variables with high collinearity and included DXA obtained Subtotal (total minus head) fat percentage and Subtotal lean mass (gms). Thereafter, we used different machine learning methods to predict maximum exercise capacity. The different machine learning models showed a strong predictive performance for both females and males. Our study shows that using baseline data from a large prospective cohort, we can predict maximum exercise capacity in persons with diabetes mellitus. We show that subtotal fat percentage is the most important feature for predicting the exercise capacity for males and females after accounting for other important variables. Until now, BMI and waist circumference were commonly used surrogates for adiposity and there was a relative under-appreciation of body composition metrics for understanding the pathophysiology of CVD. The recognition of body fat percentage as an important marker in determining CVD risk has prognostic implications with respect to cardiovascular morbidity and mortality.

scholarly journals Longitudinally evaluated the relationship between body fat percentage and the risk for type 2 diabetes mellitus: Korean Genome and Epidemiology Study (KoGES)

2018 ◽  
Vol 178 (5) ◽  
pp. 513-521 ◽  
Author(s):  
Sung Keun Park ◽  
Jae-Hong Ryoo ◽  
Chang-Mo Oh ◽  
Joong-Myung Choi ◽  
Ju Young Jung
Keyword(s):  
Diabetes Mellitus ◽  
Type 2 Diabetes ◽  
Type 2 Diabetes Mellitus ◽  
Body Fat ◽  
Subgroup Analysis ◽  
Body Fat Percentage ◽  
Fat Percentage ◽  
Specific Level ◽  
Obese Population

Background Body fat plays the significant role in maintaining glucose homeostasis. However, it is not fully identified how body fat percentage (BF%) has an impact on the development of type 2 diabetes mellitus (T2DM). Thus, this study was to evaluate the incidental risk for T2DM according to BF% level. Methods In a community-based Korean cohort, 5972 Korean adults were divided into quintile groups by BF% and followed up for 10 years to monitor the development of T2DM. Cox proportional hazard model was used to evaluate the hazard ratios (HRs) for T2DM according to BF% quintile. Additionally, subgroup analysis was conducted by low and high level of BF% (cut-off: 25 in men and 35 in women) and body mass index (BMI). Results In adjusted model, compared to the BF% quintile 1 group, the risk for T2DM significantly increased over BF% of 22.8% in men and 32.9% in women (≥quintile 4). The level of BF% related to the increased risk for T2DM was lower in non-obese men (22.8%) than obese men (28.4%). In subgroup analysis, men with low BMI (<25) and high BF% (≥25) had the highest risk for T2DM than other subgroups (HRs: 1.83 (1.33–2.52)). However, this association did not show the statistical significance in women (HRs: 1.63 (0.98–2.72)). Conclusion The incidental risk for T2DM significantly increased over the specific level of BF%, which was lower in non-obese population than obese population. Gender difference was suggested in the incidental relationship between BF% and T2DM.

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