Sagittal abdominal diameter and waist circumference appear to be equally good as identifiers of cardiometabolic risk

Increased sagittal abdominal diameter is associated with a higher risk of kidney stones

BACKGROUND

This study investigates the relationship between sagittal abdominal diameter (SAD), a measure of abdominal obesity, and kidney stone disease (KSD) in the U.S. population. Additionally, it explores potential underlying mechanisms and evaluates the clinical utility of a predictive model.

METHODS

Data were collected from 11,671 participants, including 1,136 cases of KSD. Univariate and multivariate logistic regression analyses, dose-response curves, and mediation effect assessments were employed to examine the association between SAD and KSD. A predictive model was developed and validated using calibration curves, receiver operating characteristic (ROC) curves, and clinical decision curves. Additionally, hematological indicators were analyzed to identify potential mediating factors.

RESULTS

SAD showed a strong and positive association with KSD, even after adjusting for confounders such as gender, age, and education. The predictive model demonstrated moderate accuracy (AUC =  0.661) and clinical utility. Hematological analyses indicated that granulocyte count (GRAN) significantly mediated the relationship between SAD and KSD (P <  0.001).

CONCLUSIONS

SAD is a significant risk factor for KSD, underscoring the role of abdominal obesity in kidney stone formation. The predictive model demonstrates potential clinical applications for early risk assessment and management of KSD.

Association between sagittal abdominal diameter-to-height ratio and all-cause mortality among adults in the United States: a longitudinal study

BACKGROUND

The global health crisis of obesity has prompted a need for better indicators of abdominal obesity than body mass index, with sagittal abdominal diameter emerging as a potential candidate. Nonetheless, the association between sagittal abdominal diameter-to-height ratio (SADHtR) and mortality remains inadequately established. Our objective was to contribute novel evidence to this association.

METHODS

This study encompassed 12,572 participants aged 18-80 years from the National Health and Nutrition Examination Survey 2011-2016. Mortality data were tracked until December 31, 2019. Weighted multivariable Cox proportional hazard models were employed to evaluate the association between SADHtR and all-cause mortality, with subgroup analyses conducted for result robustness.

RESULTS

Following a median follow-up period of 69 months, each standard deviation (SD) increase in SADHtR was consistently associated with a higher risk of all-cause mortality across three models, yielding a hazard ratio (HR) and 95% confidence interval (CI) of 1.51(1.29,1.76) in model 3. Additionally, compared to the first tertile of SADHtR, the third tertile exhibited a higher risk for all-cause mortality, with HRs(95%CIs) of 1.58(1.25,2.01) in model 1, 2.01(1.33,3.02) in model 2, and 1.74(1.19,2.57) in model 3. Notably, subgroup analysis revealed persistent positive associations between SADHtR and all-cause mortality among subgroups based on age-at-risk (< 65, ≥ 65 years), sex, diabetes, hypertension, and hyperlipidemia.

CONCLUSIONS

Elevated SADHtR was consistently associated with a higher risk of all-cause mortality in American adults. Regular SADHtR measurement should be considered to be integrated into clinical practice and healthcare examinations.

Obesity prediction: Novel machine learning insights into waist circumference accuracy

AIMS

This study aims to enhance the precision of obesity risk assessments by improving the accuracy of waist circumference predictions using machine learning techniques.

METHODS

We utilized data from the NHANES and Look AHEAD studies, applying machine learning algorithms augmented with uncertainty quantification. Our approach centered on conformal prediction techniques, which provide a methodological basis for generating prediction intervals that reflect uncertainty levels. This method allows for constructing intervals expected to contain the true waist circumference values with a high degree of probability.

RESULTS

The application of conformal predictions yielded high coverage rates, achieving 0.955 for men and 0.954 for women in the NHANES dataset. These rates surpassed the expected performance benchmarks and demonstrated robustness when applied to the Look AHEAD dataset, maintaining coverage rates of 0.951 for men and 0.952 for women. Traditional point prediction models did not show such high consistency or reliability.

CONCLUSIONS

The findings support the integration of waist circumference into standard clinical practice for obesity-related risk assessments using machine learning approaches.

Sagittal Abdominal Diameter as the Best Predictor of Metabolic Syndrome in HIV-Infected Men on Antiretroviral Therapy

BACKGROUND

The interaction of human immunodeficiency virus (HIV), host and antiretroviral therapy (ART) causes a range of metabolic disorders that can be characterized as a metabolic syndrome (MetS) that increases the cardiovascular risk. MetS involves central obesity, which can be detected using different anthropometric parameters.

OBJECTIVE

To assess the abilities of different anthropometric parameters in the prediction of MetS in HIV-infected men on ART.

METHOD

The study involved 92 male participants (mean age 44.46±10.38 years), divided into two groups: with and without MetS. All subjects underwent biochemical evaluation (triglycerides, HDL-cholesterol, fasting glucose), blood pressure measurement and anthropometric assessment: body mass, body height, body mass index (BMI), body fat mass, body circumferences (chest, upper arm, forearm, waist, hip, proximal and middle thigh and calf), sagittal abdominal diameter (SAD), skinfold thicknesses (subscapular, anterior and posterior upper arm, anterior and lateral forearm, abdominal, supraspinal, thigh and calf), waist-to-hip ratio (WHR), waist-to-height ratio (WHtR), waist-to-thigh ratio (WTR), sagittal abdominal diameter-to-body height ratio (SADH), body adiposity index (BAI) and conicity index. MetS was specified according to IDF criteria.

RESULTS

Subjects with MetS had statistically significant higher values of all anthropometric parameters except middle thigh circumference, calf skinfold and body height. According to ROC analysis and Binary Logistic Regression, SAD has been shown as the best predictor of MetS with a predictive value of 21.40 cm (AUC:0.91), followed by WHR with a predictive value of 0.93.

CONCLUSION

Sagittal abdominal diameter is the strongest anthropometric indicator of MetS in HIV-infected patients on ART.

Association between Body Fat Percentage and Cardiometabolic Diseases in General Population

OBJECTIVES

The body fat percentage is an indicator of overall body fat related to metabolism and inflammation. Our study aims to analyze the association between body fat percentage and the risk of cardiometabolic diseases in the general population.

METHODS

This was a retrospectively cross-sectional study. A total of 5084 participants enrolled from the National Health and Nutrition Examination Survey cycle of 1999-2004 were divided into quartiles according to their body fat percent levels. The body fat percentage was measured from bioelectrical impedance analysis. A history of cardiometabolic diseases, including cardiovascular disease, hypertension and diabetes mellitus, was ascertained from questionnaire, physical or laboratory examination. The association between body fat percentage and cardiometabolic diseases was investigated using multivariate logistic regression.

RESULTS

Compared with the lowest quartile of body fat percentage, the multivariate-adjusted odds ratio and 95% confidence interval of the highest quartile was 3.99 (1.58-10.88) for cardiovascular disease, 1.08 (1.04-1.13) for hypertension and 3.08 (1.89-5.11) for diabetes. Body fat percentage independently increased the risk of cardiometabolic diseases as a continuous variable.

CONCLUSION

Higher body fat percentage level was associated with a higher likelihood of cardiometabolic diseases, which could be a powerful predictive factor.

Cardiometabolic Profile, Physical Activity, and Quality of Life in Breast Cancer Survivors after Different Physical Exercise Protocols: A 34-Month Follow-Up Study

BACKGROUND

Breast cancer (BC) and cardiovascular (CV) disease share many risk factors associated with worse outcomes, in terms of cancer relapse, CV events, and quality of life (QoL), that could be counteracted by physical exercise (PE). We aimed to assess the impact of a 12-week differential PE protocol on cardiometabolic profile, QoL, CV- and BC-related long-term outcomes, and physical activity (PA) in a cohort of BC survivors (BCS) not treated with chemotherapy.

METHODS

57 BCS participated in a 12-week PE protocol [aerobic exercise training (AET) or resistance exercise training (RET)]. Anthropometric and CV evaluation, health-related (HR)-QoL, daily PA, cortisol, and dehydroepiandrosterone sulfate (DHEA-S) levels were assessed before (T0) and after (T1) PE. We assessed BC and CV outcomes, HR-QoL, CV-QoL, and PA at the follow-up.

RESULTS

RET improved waist circumference, DHEA-S, cortisol/DHEA-S, systolic and mean blood pressure, and ventricular/arterial coupling; AET ameliorated sagittal abdomen diameter and pulse wave velocity. Regarding HR-QoL, physical function improved only in AET group. At a mean 34 ± 3.6-month follow-up, we documented no significant differences in CV-QoL, HR-QoL, and PA or CV and BC outcomes.

CONCLUSIONS

AET and RET determine specific, positive adaptations on many parameters strongly related to CV risk, CV and BC outcomes, and QoL, and should be included in any cardio-oncology rehabilitation program.

Effects of Aerobic Exercise Concurrent with Caffeine Supplementation on Weight and Body Fat Among Overweight Women

Background: Obesity and overweight are among serious global epidemics that significantly threaten human health, especially among women. Objectives: This study aimed to assess the concurrent effects of 6-week caffeine supplementation with moderate-intensity aerobic exercise on weight and body fat among overweight women. Methods: Thirty overweight females (age: 36.47 ± 6.48 years; BMI: 27.61 ± 1.54 kg/m2; mean ± SD) with a sedentary lifestyle were recruited to the study. The participants were randomly allocated to the experimental group, EC (exercise + caffeine) group, who took 100 milligrams of caffeine of the “API” brand supplement 30 minutes before exercise training (n = 15) or control group, EP (exercise + placebo) (n = 15). All participants performed moderate-intensity aerobic exercise with an intensity of 40 to 60% of heart rate reserve based on the individual's exercise test for 30 minutes, three days a week for six weeks. Measurements, including the percentage of body fat, waist circumference, and skinfold (suprailiac, abdominal), were done two times, at baseline and after six weeks of exercising. Results: There were no significant differences between control and experimental groups related to weight (P = 0.22), percentage body fat (P = 0.88), and other measurements after six weeks. Conclusions: 6 weeks of caffeine supplementation combined with moderate-intensity aerobic exercise without dietary interventions couldn’t make a significant reduction in weight and central or total body fat among overweight women.

Estimating trunk fat in children according to sex using basic somatic readings: an opportunity for improving evaluation among girls

BACKGROUND

The fat mass estimators waist-to-height ratio (WHtR) and relative fat mass-pediatric (RFMp) complement the widely accepted body mass index (BMI) in obesity evaluation.

AIMS OF THE STUDY

Conduct an easy appraisal of trunk fat and the cardiometabolic risk associated with pediatric obesity.

METHODS

A total of 472 children (39% boys in the total sample) were classified as underweight, normal weight, overweight or obese (nutritional groups, NGs) according to BMI Z-score after initial anthropometric data were obtained and ad hoc exclusion criteria were applied. WHtR and RFMp (% of total fat) were calculated for each group, associations were assessed through multiple linear regression (MLR), and differences between sexes were evaluated (medians, IQR).

RESULTS

The mean age (mean (95% CI)) was 10.8 y (10.1-11.1). The values in the total sample were as follows: WHtR, 0.5 (0.49-0.51) and RFMp%, 32.3 (31.7-33.0). In the overweight group, the values were as follows: WHtR, 0.51 (0.50-0.52) and RFMp(%), 34.2 (33.3-35.1). In the obese group, the values were as follows: WHtR, 0.56 (0.55-0.57) and RFMp(%), 37.8 (36.9-38.6). The associations were as follows (NG; independent variables): In the NG, adjusted R2 values were between 0.74 and 0.78. In the total sample, the beta coefficient was 3.36 (P < 0.001) for RFMp for girls; for waist circumference (WC), the beta coefficient was 2.97 (P < 0.001), and for WHtR the beta coefficients were - 0.01 (p < 0.001) and 0.03 (p < 0.001),for girls and for WC respectively. The sex differences were as follows: BMI exhibited no differences in the NG (Mann-Whitney U). WHtR (median (IQR)) differed (M vs. F) in the total sample (0.49 (0.45-0.54) vs. 0.52 (0.45-0.56), p < 0.004); in the overweight group (0.51 (0.48-0.53) vs. 0.54 (0.51-0.55), p < 0.001); and in the obese group (0.55 (0.52-0.57) vs. 0.57 (0.54-0.60), p < 0.004). RFMp (%) differed in the total group (29.21 (24.27-32.92) vs. 36.63 (30.2-39.51), p < 0.001); in the overweight group (31.24 (28.35-32.35) vs. 37.95 (35.75-38.82), p < 0.001) and in the obese group (35.89 (32.05-36.15) vs. 40.63 (38.27-42.42), p < 0.001).

CONCLUSIONS

WHtR and RFMp are simple and reliable indices that do not require centile charts. Their values, including waist circumference, can be used to estimate the different trunk fat components in boys and girls better than BMI, especially if individuals are overweight or obese. RFMp proved to be more reliable as it considers sex. Both should be included in routine anthropometric readings.

The Prevalence, Popular Trends, and Associated and Predictive Factors of Non-Obese Fatty Liver Disease

BACKGROUND AND AIMS

There are few studies on non-obese fatty liver disease, the aims of this study was to analyze its prevalence, popular trends, and associated and predictive factors, so as to provide reference for its prevention and treatment.

METHODS

Individuals with complete data of body mass index, sex, age, and abdominal ultrasound in Karamay Central Hospital from 2009 to 2016 were selected to analyze the prevalence and popular trends of non-obese fatty liver disease (body mass index <24 kg/m2), and associated and predictive factors.

RESULTS

Between 2009 and 2016, a total of 191,555 medical check-ups were included. The prevalence of non-obese fatty liver disease increased from 1.9% to 5.1% among general medical examinants (P<0.001), increased from 4.6% to 11.7% in non-obese individuals (P<0.001). Compared with the non-obese control group, the levels of age, body mass index, blood pressure, fasting blood glucose, triglycerides, total cholesterol and uric acid in the non-obese fatty liver group were higher (P<0. 05). Even among non-obese subjects, elevated body mass index was associated with a 0.63-fold increased risk for non-obese fatty liver disease (P<0.001, odds ratio=1.63, 95% confidence interval 1.54-1.72) for every one-unit increase in body mass index. The most common abnormal indicator of non-obese fatty liver disease was elevated triglycerides (44.2%), which was also the best predictor of non-obese fatty liver disease (area under the curve =0.795) in non-obese physical examinators.

CONCLUSIONS

The prevalence of non-obese fatty liver disease was high and increasing rapidly in Karamay. Triglycerides is the best predictor of non-obese fatty liver in non-obese physical examinators.