Identifying the waist circumference of risk in people of African descent

A Combined Region- and Pixel-Based Deep Learning Approach for Quantifying Abdominal Adipose Tissue in Adolescents Using Dixon Magnetic Resonance Imaging

BACKGROUND

The development of adipose tissue during adolescence may provide valuable insights into obesity-associated diseases. We propose an automated convolutional neural network (CNN) approach using Dixon-based magnetic resonance imaging (MRI) to quantity abdominal subcutaneous adipose tissue (SAT) and visceral adipose tissue (VAT) in children and adolescents.

METHODS

474 abdominal Dixon MRI scans of 136 young healthy volunteers (aged 8-18) were included in this study. For each scan, an axial fat-only Dixon image located at the L2-L3 disc space and another image at the L4-L5 disc space were selected for quantification. For each image, an outer and an inner region around the abdomen wall, as well as SAT and VAT pixel masks, were generated by expert readers as reference standards. A standard U-Net CNN architecture was then used to train two models: one for region segmentation and one for fat pixel classification. The performance was evaluated using the dice similarity coefficient (DSC) with fivefold cross-validation, and by Pearson correlation and the Student's t-test against the reference standards.

RESULTS

For the DSC results, means and standard deviations of the outer region, inner region, SAT, and VAT comparisons were 0.974 ± 0.026, 0.997 ± 0.003, 0.981 ± 0.025, and 0.932 ± 0.047, respectively. Pearson coefficients were 1.000 for both outer and inner regions, and 1.000 and 0.982 for SAT and VAT comparisons, respectively (all p = NS).

CONCLUSION

These results show that our method not only provides excellent agreement with the reference SAT and VAT measurements, but also accurate abdominal wall region segmentation. The proposed combined region- and pixel-based CNN approach provides automated abdominal wall segmentation as well as SAT and VAT quantification with Dixon MRI and enables objective longitudinal assessment of adipose tissues in children during adolescence.

Associations of body shapes with insulin resistance and cardiometabolic risk in middle-aged and elderly Chinese

Background

We aimed to define refined body shapes by using multiple anthropometric traits that represent fat distribution, and evaluate their associations with risk of insulin resistance (IR) and cardiometabolic disorders in a Chinese population.

Methods

We performed a cross-sectional analysis in 6570 community-based participants aged ≥ 40 years. Four body circumferences (neck, waist, hip, and thigh) and their ratios were put simultaneously into an open-source Waikato Environment for Knowledge Analysis platform to select the worthiest indicators in determining IR. The ratio of the top 3 fat distribution indicators was used to define the refined body shapes.

Results

We defined 8 distinct body shapes based on sex-specific combinations of waist-to-hip ratio (WHR), waist-to-thigh ratio (WTR), and waist-to-neck ratio (WNR), which differed in participants’ distribution and risk of IR and related cardiometabolic disorders. In women, as compared to the low WHR-low WTR-low WNR shape, all body shapes were significantly associated with IR and related cardiometabolic disorders; while in men, the low WHR-high WTR-high WNR shape and the higher WHR related shapes were significantly associated with IR and related cardiometabolic disorders. Stratified by WHR, the results were consistent in women; however, no significant associations were detected in men.

Conclusions

We defined 8 distinct body shapes by taking WHR, WTR, and WNR, simultaneously into account, which differed in association with the risk of IR and related cardiometabolic disorders in women. This study suggests that body shapes defined by multiple anthropometric traits could provide a useful, convenient, and easily available method for identifying cardiometabolic risk.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12986-021-00629-1.

The Effects of Asthma on the Association Between Pulmonary Function and Obesity: A 16-Year Longitudinal Study

Background

Asthma and obesity are important public health issues around the world. Obesity is considered a risk factor associated with the severity and incidence of asthma. We investigated the relationships between poor pulmonary function (defined by forced vital capacity (FVC) and percentage of predicted FVC (FVC%)) and obesity.

Methods

This is a retrospective longitudinal study using the MJ health examination database in Taiwan from 2000 to 2015. There were 160,609 participants aged ≥20 years with complete obesity indicators and lung function data, and having at least two visits. A generalized estimation equation (GEE) model was applied to estimate the association between lung function and obesity.

Results

BMI was the best indicator to predict poor pulmonary function for our participants. Results of BMI are presented as an example: Obesity (body mass index (BMI) ≥27.0 kg/m²) is significantly associated with lower FVC [adjusted coefficients (β) for asthmatics: -0.11 L (95% CI: -0.14, -0.08); adjusted β for non-asthmatics: -0.08 L (-0.09, -0.08)] and FVC% [adjusted β for asthmatics: -1.91% (95% CI: -2.64, -1.19); adjusted β for non-asthmatics: 1.48% (-1.63, -1.33)]. Annual change of BMI (ΔBMI/year) is an independent risk factor for decreased FVC [adjusted β for asthmatics: -0.030 L (-0.048, -0.013); adjusted β for non-asthmatics: -0.019 L (-0.022, -0.016)] and FVC% [adjusted β for non-asthmatics: -0.603% (-1.063, -0.142); adjusted β for non-asthmatics: -0.304% (-0.393, -0.214)], and is significantly associated with accelerated FVC decline [adjusted β of ΔFVC/year and ΔFVC %/year for asthmatics: -0.038 L (-0.054, -0.022) and -0.873% (-1.312, -0.435); adjusted β of ΔFVC/year and ΔFVC %/year for non-asthmatics: -0.033 L (-0.042, -0.024) and -0.889% (-1.326, -0.452)].

Conclusion

Obesity is significantly associated with decreased lung function, and asthmatics had a higher risk than non-asthmatics.

A Stress Syndrome Prototype Reflects Type 3 Diabetes and Ischemic Stroke Risk: The SABPA Study

Type 3 diabetes (T3D) accurately reflects that dementia, e.g., Alzheimer's disease, represents insulin resistance and neurodegeneration in the brain. Similar retinal microvascular changes were observed in Alzheimer's and chronic stressed individuals. Hence, we aimed to show that chronic stress relates to T3D dementia signs and retinopathy, ultimately comprising a Stress syndrome prototype reflecting risk for T3D and stroke. A chronic stress and stroke risk phenotype (Stressed) score, independent of age, race or gender, was applied to stratify participants (N = 264; aged 44 ± 9 years) into high stress risk (Stressed, N = 159) and low stress risk (non-Stressed, N = 105) groups. We determined insulin resistance using the homeostatic model assessment (HOMA-IR), which is interchangeable with T3D, and dementia risk markers (cognitive executive functioning (cognitiveexe-func); telomere length; waist circumference (WC), neuronal glia injury; neuron-specific enolase/NSE, S100B). Retinopathy was determined in the mydriatic eye. The Stressed group had greater incidence of HOMA-IR in the upper quartile (≥5), larger WC, poorer cognitiveexe-func control, shorter telomeres, consistently raised neuronal glia injury, fewer retinal arteries, narrower arteries, wider veins and a larger optic cup/disc ratio (C/D) compared to the non-Stressed group. Furthermore, of the stroke risk markers, arterial narrowing was related to glaucoma risk with a greater C/D, whilst retinal vein widening was related to HOMA-IR, poor cognitiveexe-func control and neuronal glia injury (Adjusted R2 0.30; p ≤ 0.05). These associations were not evident in the non-Stressed group. Logistic regression associations between the Stressed phenotype and four dementia risk markers (cognitiveexe-func, telomere length, NSE and WC) comprised a Stress syndrome prototype (area under the curve 0.80; sensitivity/specificity 85%/58%; p ≤ 0.001). The Stress syndrome prototype reflected risk for HOMA-IR (odds ratio (OR) 7.72) and retinal glia ischemia (OR 1.27) and vein widening (OR 1.03). The Stressed phenotype was associated with neuronal glia injury and retinal ischemia, potentiating glaucoma risk. The detrimental effect of chronic stress exemplified a Stress syndrome prototype reflecting risk for type 3 diabetes, neurodegeneration and ischemic stroke.