Comparison of obesity and metabolic syndrome prevalence using fat mass index, body mass index and percentage body fat

Associations of obesity defined comprehensively by body mass index and body fat percentage with osteopenia

OBJECTIVE

To explore the association of obesity comprehensively defined by Body Mass Index (BMI) and Body Fat percentage (BF%) with osteopenia.

METHODS

In this cross-sectional study, data of adult men and postmenopausal women aged ≥ 50 years old were obtained from the National Health and Nutrition Examination Surveys (NHANES) database. Weighted logistic regression analysis was conducted to investigate the association of BF% obesity with osteopenia in participants who had different gender and BMI obesity conditions. The association of obesity comprehensively evaluated by BMI and BF% with osteopenia was also explored in the total population and in gender subgroups.

RESULTS

Among 1720 eligible subjects, 1054 had osteopenia. Multivariate analysis suggested that in males, BMI obesity combined with BF% obesity was associated with higher osteopenia odds compared to BMI obesity only (Odds Ratio [OR = 4.01], 95% Confidence Interval [95% CI 1.43‒11.27]). Compared to participants with both BMI and BF% obesity, those with BMI obesity have lower osteopenia odds (OR = 0.46, 95% CI 0.28‒0.76), whereas those with BF% obesity have higher odds of osteopenia (OR = 2.03, 95% CI 1.35‒3.05, p = 0.002). In females, compared to BMI obesity combined with BF% obesity, BF% obesity (OR = 3.37, 95% CI 1.47‒7.73) or non-obesity (OR = 2.11, 95% CI 1.18‒3.75) was respectively associated with higher osteopenia odds. In males, BMI obesity was linked to lower osteopenia odds compared to both BMI and BF% obesity (OR = 0.25, 95% CI 0.10‒0.62).

CONCLUSIONS

The comprehensively assessed obesity by BMI and BF% may be more meaningful in the evaluation of potential osteopenia risk, as well as further prevention and intervention of osteoporosis.

Relationship of fat mass index and fat free mass index with body mass index and association with sleeping patterns and physical activity in Saudi young adults women

AIM

To analyze the association between Fat Mass Index (FMI), Free Fat Mass Index (FFMI), Free Fat Mass/Fat Mass (FFM/FM), and Body Mass Index (BMI) among young adult Saudi women and to explore how these body composition indices are associated with sleep and physical activity patterns.

METHODS

A total of 1,741 university female students participated in this cross-sectional study. Body composition was measured using the InBody 270 body composition analyzer. FMI, FFMI, and FM/FFM were classified into tertiles (T1, T2, T3), with T1 classified as the lowest and T3 as the highest tertile. Sleep quality and duration were assessed using the Pittsburgh Sleep Quality Index, while physical activity was measured using an exercise vital sign tool.

RESULTS

BMI increased significantly from Tertile 1 to Tertile 3 across all groups for FMI and FFMI (p < 0.001), while a decrease in FM/FFM was observed across tertiles (p < 0.001). Conversely, FFM was highest in the third tertile of FFMI (p < 0.001). No significant associations were found between sleep duration or quality and body composition indices, even after adjusting for age and BMI. However, significant associations were observed between physical activity frequency and duration and body composition, particularly FFMI and FMI. These associations became more pronounced after adjusting for age and BMI.

CONCLUSION

The findings highlight a strong association between physical activity patterns and body composition indices, particularly FFMI and FMI, among young adult Saudi women. While sleep patterns did not show significant relationships with body composition, the results emphasize the importance of regular physical activity in maintaining healthy body composition. These insights underline the need for targeted interventions promoting physical activity to support optimal health and well-being in this population.

Sarcopenic obesity and brain health: A critical appraisal of the current evidence

Sarcopenic obesity (SO) is a body composition phenotype derived from the simultaneous presence in the same individual of an increase in fat mass and a decrease in skeletal muscle mass and/or function. Several protocols for the diagnosis of SO have been proposed in the last two decades making prevalence and disease risk estimates of SO heterogeneous and challenging to interpret. Dementia is a complex neurological disorder that significantly impacts patients, carers and healthcare systems. The identification of risk factors for early cognitive impairment and dementia is key to mitigating the forecasted trends of a 2-fold increase in dementia case numbers over the next two decades worldwide. Excess adiposity and sarcopenia have both been independently associated with risk of cognitive impairment and dementia. Whether SO is associated with a greater risk of cognitive impairment and dementia is currently uncertain. This review critically appraises the current evidence on the association between SO with cognitive outcomes and dementia risk. It also discusses some of the putative biological mechanisms that may link the SO phenotype with alteration of brain functions.

Prevalence of metabolic syndrome and its association with selected factors among people with psychiatric conditions in Ethiopia: a systematic review and meta-analysis

BACKGROUND

Metabolic syndrome is a cluster of metabolic risk factors, including glucose intolerance, dyslipidemia, central obesity, high triglyceride levels, and low levels of high-density lipoprotein. It is the commonest type of co-morbidity among people with psychiatric conditions particularly in low and middle-income countries due to poor health care systems and financial burden. Metabolic syndrome among people with psychiatric conditions may be due to prolonged use of psychiatric medications, diminished quality of life, and personal and behavioral-related factors. Except for single studies with fluctuating reports, there is no nationwide study conducted on the prevalence of metabolic syndrome among people with psychiatric conditions in Ethiopia. Thus, this review aims to estimate the pooled prevalence of metabolic syndrome and its association with selected factors among people with psychiatric conditions in Ethiopia.

METHODS

We conducted a thorough search of PubMed, Scopus, Wiley online library, African journals online, and Google Scholar. For analysis, STATA version 14 software was used. A funnel plot and Egger's regression test statistic were used to find the potential reporting bias. A fixed effect model was used to contrast summary effects, odds ratios, and 95% confidence intervals all over research findings. The Newcastle-Ottawa Scale (NOS) was used to evaluate the quality of each included study.

RESULTS

Eight articles were included in the final review after retrieving 9,714 articles through electronic database searching. By using the national cholesterol education adult treatment panel criteria, the pooled prevalence of metabolic syndrome among people with psychiatric conditions in Ethiopia was found to be 37.33% (95%CI: 24.52-50.14). Being female AOR = 2.66; 95% CI: 0.89, 7.92), urban residency (AOR = 2.84; 95% CI: 0.56, 14.45), physical inactivity (AOR = 3.80; 95% CI: 1.61, 8.98), alcohol consumption (AOR = 4.53; 95% CI: 1.62, 12.71) and body mass index higher than the normal range (AOR = 4.66; 95% CI: 1.22, 17.85) were the factors significantly associated with metabolic syndrome among people with psychiatric conditions. According to the review, schizophrenic-form disorder, delusional disorder, major depressive disorder, schizophrenia, bipolar disorder, and schizoaffective disorder were the frequently reported psychiatric conditions.

CONCLUSION

This systematic review and meta-analysis revealed that the magnitude of metabolic syndrome among people with psychiatric conditions in Ethiopia was high and female gender, physical inactivity, alcohol consumption, and body mass index higher than the normal range were the factors that determined the occurrence of metabolic syndrome. Thus, policymakers, clinicians, and other concerned stakeholders must reinforce effective strategies in the control, timely screening, prevention, and management of metabolic syndrome among people with psychiatric conditions.

PROTOCOL REGISTRATION

PROSPERO CRD42023405293.

Assessing the prevalence of obesity in a Russian adult population by six indices and their associations with hypertension, diabetes mellitus and hypercholesterolaemia

The anthropometric index that best predicts cardiometabolic risk remains inconclusive. This study therefore assessed the prevalence of obesity using six indices and compared their associations with obesity-related cardiometabolic disorders. We determined obesity prevalence according to body mass index, waist circumference, waist-to-hip ratio, waist-to-height ratio (WHtR), body fat percentage and fat mass index (FMI) using data from the Know Your Heart study (n = 4495, 35-69 years). The areas under the receiver operating characteristic curves (AUCs) provided predictive values of each index for detecting the presence of hypertension, hypercholesterolaemia and diabetes. Age-standardised obesity prevalence significantly varied according to anthropometric index: from 17.2% (FMI) to 75.8% (WHtR) among men and from 23.6% (FMI) to 65.0% (WHtR) among women. WHtR had the strongest association with hypertension (AUC = 0.784; p < 0.001) and with a combination of disorders (AUC = 0.779; p < 0.001) in women. In women, WHtR also had the largest AUCs for hypercholesterolaemia, in men - for hypertension, diabetes and a combination of disorders, although not all the differences from other obesity indices were significant. WHtR exhibited the closest association between hypertension and a combination of disorders in women and was non-inferior compared to other indices in men.

Narrative review of lifestyle interventions in breast cancer survivors: current evidence and future directions

BACKGROUND

In 8 females, 1 will be diagnosed with breast cancer in their lifetime. Although medical advances have increased the likelihood of survival, up to 90% of females will gain weight during and after treatment increasing the risk of breast cancer recurrence and obesity-related comorbidities in survivorship. Behavioral lifestyle interventions focused on diet with or without physical activity can provide breast cancer survivors nonpharmacological options to decrease weight gain and cardiometabolic risk.

METHOD

A PubMed search was conducted to identify all behavioral lifestyle interventions focused on diet or diet combined with physical activity longer than 4 weeks of duration in breast cancer survivors that included body weight as an outcome. This review aims to summarize the effects on body weight, body composition, and cardiometabolic risk markers.

RESULTS

The review shows there is high heterogeneity in type and duration of the intervention to affect weight and cardiometabolic risk in survivorship. Calorie restriction with and without physical activity appears to promote weight loss among breast cancer survivors. However, the effects on cardiometabolic factors are less clear.

CONCLUSIONS

Future studies should be powered for body weight and cardiometabolic effects. Researchers should also consider interventions that (1) are less complex, (2) recruit a more racially and ethnically diverse sample, (3) integrate resistance training, (4) implement the intervention in closer proximity to diagnosis, (5) target weight management in this population before it occurs, and (6) analyze body composition in addition to body weight measurements.

Modeling health risks using neural network ensembles

This study aims to demonstrate that demographics combined with biometrics can be used to predict obesity related chronic disease risk and produce a health risk score that outperforms body mass index (BMI)-the most commonly used biomarker for obesity. We propose training an ensemble of small neural networks to fuse demographics and biometrics inputs. The categorical outputs of the networks are then turned into a multi-dimensional risk map, which associates diverse inputs with stratified, output health risk. Our ensemble model is optimized and validated on disjoint subsets of nationally representative data (N~100,000) from the National Health and Nutrition Examination Survey (NHANES). To broaden applicability of the proposed method, we consider only non-invasive inputs that can be easily measured through modern devices. Our results show that: (a) neural networks can predict individual conditions (e.g., diabetes, hypertension) or the union of multiple (e.g., nine) health conditions; (b) Softmax model outputs can be used to stratify individual- or any-condition risk; (c) ensembles of neural networks improve generalizability; (d) multiple-input models outperform BMI (e.g., 75.1% area under the receiver operator curve for eight-input, any-condition models compared to 64.2% for BMI); (e) small neural networks are as effective as larger ones for the inference tasks considered; the proposed models are small enough that they can be expressed as human-readable equations, and they can be adapted to clinical settings to identify high-risk, undiagnosed populations.

Impact of sarcopenia and obesity on overall survival in patients with head and neck cancer receiving radiotherapy: A longitudinal study

PURPOSE

To analyze the impact of sarcopenia and obesity on overall survival (OS) in patients with head and neck cancer (HNC) receiving radiotherapy (RT).

METHODS

This prospective longitudinal study recruited 494 patients using convenient sampling. Weight and body composition were assessed before RT (T1), and at the end of RT (T2) using bioelectrical impedance analysis (BIA). The appendicular skeletal mass index was used to define sarcopenia, while the body mass index and fat mass index were used to define obesity. Patient OS was followed and described using Kplan-Meier analysis. Cox proportional hazard regression was used to analyze influencing factors of OS.

RESULTS

The median follow-up time was 26.2 months (IQR: 18.4-34.4 months). Multivariable models indicated that sarcopenia/obesity type assessed at T1 was not significantly associated with OS. Multivariable models involving body composition at T2 showed that age (P < 0.001), tumor site (P = 0.003), tumor stage (P = 0.024), and sarcopenia/obesity type (P = 0.040) were significantly associated with OS, while sarcopenic patients without obesity at T2 had worse OS.

CONCLUSIONS

Patients with sarcopenia and no obesity at the end of RT might have worse OS. Healthcare professionals should enhance HNC patients' management during RT, helping them maintain a certain amount of muscle mass and fat mass to improve their survival.

Nonlinear relationship between cardiometabolic index and bone mineral density in U.S. adults: the mediating role of percent body fat

BACKGROUND

Both lipid metabolism and obesity are crucial factors in osteoporosis, influencing the relevance of the cardiometabolic index (CMI), a new body fat index incorporating obesity and lipid metrics. Our study aims to explore the relationship between CMI and lumbar spine bone mineral density (BMD) and the mediating role of body fat percentage.

METHODS

Utilizing the National Health and Nutrition Examination Survey (NHANES) data from 2011 to 2018, we conducted a cross-sectional analysis. We employed multiple linear regression models, subgroup analyses, generalized additive models (GAM), smooth curve fitting, and mediation analysis to evaluate the linear and nonlinear relationships between CMI and lumbar spine BMD.

RESULTS

The study involved 5,124 participants with an average lumbar spine BMD of 1.03 ± 0.15 g/cm2. We identified a negative correlation between CMI and lumbar spine BMD (β = -0.015; 95% CI: -0.023, -0.008). Nonlinear associations were evident, with inflection points at CMI values of 1.12 and 2.86. Subgroup analyses showed consistent negative correlations across all categories without significant differences (p for interaction > 0.05). Moreover, body fat percentage negatively correlated with BMD (β = -0.005; 95% CI: -0.006, -0.004) and mediated 9.41% of the relationship between CMI and BMD.

CONCLUSION

Increased CMI levels are associated with lower lumbar spine BMD, with body fat percentage significantly mediating this relationship. This underscores the importance of managing body composition in the context of bone health, highlighting CMI's potential utility in osteoporosis risk assessment.

The Role of Diet and Physical Activity in Obesity and Overweight in Children with Down Syndrome in Developed Countries

Down's syndrome (DS), or Trisomy 21, represents the most common chromosomal abnormality in live births, characterized by an extra chromosome 21. Children affected by Down's syndrome are more susceptible to the development of obesity and of becoming overweight compared with other children. Furthermore, they seem to present a more unfavorable lipid profile than the non-DS obese pediatric population. Diet and physical activity are closely related to the development of overweight and obesity, and they can be assessed using questionnaires such as the Mediterranean Diet Quality Index in children and adolescents (KIDMED) and the Godin-Shephard Leisure-Time Physical Activity Questionnaire. This review aims to undertake a comprehensive analysis of the intricate interplay between diet and physical activity in children affected by Down's syndrome. Specifically, it seeks to deepen understanding regarding the question of how diet and exercise can influence and prevent the development of overweight and obesity in that special pediatric population.

Association of hypertriglyceridemic waist phenotype with metabolic syndrome traits and its diagnostic potential to predict metabolic syndrome in adults with excess body weight: A community-based cross-sectional study

BACKGROUND

The hypertriglyceridemic waist (HTGW) phenotype is a simple measure to identify individuals at increased risk of metabolic syndrome (MetS) traits. The present study aimed to describe the HTGW prevalence, and its associations with MetS traits, and also determine the diagnostic potential of the mirror indices of HTGW phenotype to predict MetS and its components in community-dwelling adults with overweight or obesity in Southern, Sri Lanka.

METHODS

In a cross-sectional study, 300 adults with excess body weight (body mass index >23 kg/m2) were enrolled and examined for the HTGW phenotype (fasting plasma triglyceride concentration ≥1.695 mmol/L and waist circumference >90 and >85 cm in males and females, respectively).

RESULTS

One in five adults with excess body weight had the HTGW phenotype. Phenotype-positive adults had significantly higher fasting plasma glucose (FPG) (p = 0.010), low-density lipoprotein cholesterol (HDL-C) (p < 0.001), total cholesterol (p < 0.001), atherogenic index (p < 0.001), coronary risk index (p = 0.001), triglyceride glucose index (p = 0.040), bioimpedance visceral fat (p = 0.041) and significantly lower HDL-C (p = 0.001) and cardioprotective index (p = 0.009) than those without the HTGW phenotype. Adults with excess body weight and the HTGW phenotype had an increased risk of FPG (odds ratio [OR] = 1.294; 95% confidence interval [CI] 1.051-1.594), atherogenic index (OR = 3.138; 95% CI = 1.559-6.317) and triglyceride glucose index (OR = 3.027; 95% CI = 1.111-8.249). The HTGW phenotype was strongly associated with MetS traits (OR = 16.584; 95% CI = 6.230-44.147). The cut-off values for the product of waist circumference × triglyceride, to identify the risk of having MetS and dyslipidemia among adults with excess body weight were 158.66 and 160.15 cm × mmol/L, respectively.

CONCLUSIONS

The readily available and inexpensive measures of the HTGW phenotype could serve as a clinically useful marker to identify MetS traits in adults with excess body weight.

Predictive values of relative fat mass and body mass index on cardiovascular health in community-dwelling older adults: Results from the Longevity Check-up (Lookup) 7

OBJECTIVES

To assess the predictive value of relative fat mass compared to body mass index for hypertension, diabetes, hyperlipidemia, and heightened cardiovascular risk in a cohort of community-dwelling older adults from the Longevity Check-up 7+ cohort.

STUDY DESIGN

Retrospective cross-sectional study.

MAIN OUTCOME MEASURES

Hyperlipidemia was defined as total cholesterol ≥200 mg/dL or ongoing lipid-lowering treatment. Diabetes was defined either as self-reported diagnosis or fasting blood glucose >126 mg/dL or a random blood glucose >200 mg/dL. Hypertension was defined as blood pressure ≥ 140/90 mmHg or requiring daily antihypertensive medications. Heightened cardiovascular risk was operationalized as having at least two of these conditions.

RESULTS

Analyses were conducted in 1990 participants (mean age 73.2 ± 6.0 years; 54.1 % women). Higher proportions of men than women had hypertension and diabetes, while hyperlipidemia was more prevalent in women. Receiver operating curve analysis indicated relative fat mass was a better predictor of hypertension in women and diabetes in both sexes. Body mass index performed better in predicting hyperlipidemia in women. Relative fat mass thresholds of ≥27 % for men and ≥40 % for women were identified as optimal indicators of heightened cardiovascular risk and so were used to defined high adiposity. Moderate correlations were found between high adiposity or body mass index ≥25 kg/m2 and the presence of hypertension, hyperlipidemia and heightened cardiovascular risk, while a strong correlation was found with diabetes. Logistic regression analysis highlighted significant associations between high adiposity and increased odds of hypertension, diabetes, and heightened cardiovascular risk.

CONCLUSIONS

Proposed cut-offs for relative fat mass were more reliable indices than the usual cut-offs for body mass index for identifying individuals at heightened cardiovascular risk. Our findings support the role of anthropometric measures in evaluating body composition and the associated metabolic and cardiovascular conditions in older adults.

Revealing Molecular Mechanisms of the Bioactive Saponins from Edible Root of Platycodon grandiflorum in Combating Obesity

Obesity has emerged as a significant health concern, as it is a disease linked to metabolic disorders in the body and is characterized by the excessive accumulation of lipids. As a plant-derived food, Platycodon grandiflorum (PG) was reported by many studies, indicating that the saponins from PG can improve obesity effectively. However, the anti-obesity saponins from PG and its anti-obesity mechanisms have not been fully identified. This study identified the active saponins and their molecular targets for treating obesity. The TCMSP database was used to obtain information on 18 saponins in PG. The anti-obesity target of the PG saponins was 115 targets and 44 core targets. GO and KEGG analyses using 44 core anti-obesity genes and targets of PG-active saponins screened from GeneCards, OMIM, Drugbank, and DisGeNet showed that the PI3K-Akt pathway, the JAK-STAT pathway, and the MAPK pathway were the major pathways involved in the anti-obesity effects of PG saponins. BIOVIA Discovery Studio Visualizer and AutoDock Vina were used to perform molecular docking and process the molecular docking results. The molecular docking results showed that the active saponins of PG could bind to the major therapeutic obesity targets to play an obesity-inhibitory role. The results of this study laid the foundation for further research on the anti-obesity saponins in PG and their anti-obesity mechanism and provided a new direction for the development of functional plant-derived food. This research studied the molecular mechanism of PG saponins combating obesity through various signaling pathways, and prosapogenin D can be used to develop as a new potential anti-obesity drug.

Exploring the role of sex in the association of late chronotype on cardiorespiratory fitness

Circadian rhythms differ between young adult males and females. For example, males tend to be later chronotypes, preferring later timing of sleep and activity, than females. Likewise, there are sex differences in body composition and cardiorespiratory fitness. Few studies have investigated the association between circadian rhythms, cardiorespiratory fitness, and body composition. We sought to determine whether chronotype and circadian phase were associated with cardiorespiratory fitness, body composition, and anthropometric measures in sedentary males and females. Fifty-nine adults participated in the study. Circadian phase and chronotype were measured using dim light melatonin onset (DLMO) and the Morningness-Eveningness Questionnaire (MEQ) score. We used peak oxygen uptake (VO2peak ) results from a maximal graded exercise test to assess cardiorespiratory fitness. Body composition, BMI, and circumferences were collected as markers of adiposity. We observed a sex difference in the association between DLMO and VO2peak . For males, a later DLMO was associated with a lower VO2peak . VO2peak did not vary based on DLMO in females. Later circadian phase was also associated with increased body fat percentage, fat mass index, and abdominal circumference in males, but not females. Collectively, these results suggest that males who are later chronotypes may be at risk of obesity and low cardiorespiratory fitness.

Assessment of the performance of the body mass index in diagnosing obesity in community-dwelling older adults in Latin American and Caribbean countries

BACKGROUND

The body mass index (BMI) ≥30 kg/m2 is the universally accepted cut-off point for defining obesity; however, its accuracy in classifying obesity in older adults is poorly understood.

OBJECTIVES

To assess the performance of the BMI cut-off point ≥30 kg/m2 in classifying obesity in older adults, using the fat mass index (FMI) and fat mass percentage (FM%) as reference criteria; and to establish region- and sex-specific BMI-based cut-off points to classify obesity in older adults.

METHODS

The present study is a secondary analysis derived from a cross-sectional project that included a sample of 1463 older adults from ten Latin American and Caribbean countries. Volunteers underwent total body water measurements using the deuterium dilution technique to determine FMI and FM%. Accuracy of the BMI and derived cutoff points was assessed by the area under the receiver operating characteristic curve (AUC).

RESULTS

The BMI cut-off point ≥30 kg/m2 had low sensitivity for classifying obesity in these older adults compared to the FMI and FM%. The AUC values for the optimal BMI-derived cut-off points showed an acceptable-to-outstanding discriminatory capacity in diagnosing obesity defined by the FMI. There was also a better balance between sensitivity and specificity than with the values obtained by a BMI ≥30 kg/m2 in older subjects in both regions.

CONCLUSION

The BMI cut-off point ≥30 kg/m2 had poor sensitivity for accurately diagnosing obesity in older adults from two regions. The region- and sex-specific BMI-derived cut-off points for defining obesity using the FMI are more accurate in classifying obesity in older men and women subjects from both regions.

A high Diabetes Risk Reduction Score (DRRS) is associated with a better cardio-metabolic profile among obese individuals

BACKGROUND

Dietary indices and scores are valuable predictive markers against chronic diseases. Several previous studies have revealed the beneficial effects of diabetes risk reduction score (DRRS) against diabetes and cancer incidence. However, its association with metabolic abnormalities among obese individuals have not been revealed before. In the current study, we aimed to investigate the association between DRRS and metabolic risk factors among obese individuals.

METHODS

In the current cross-sectional study, 342 obese individuals [Body mass index (BMI) ≥ 30 kg/m2] aged 20-50 years were included. Dietary intake was assessed by a validated semi-quantitative food frequency questionnaire (FFQ) of 168 food items and DRRS was calculated. Metabolic syndrome (MetS) was defined based on the guidelines of the National Cholesterol Education Program Adult Treatment Panel III (NCEP-ATP III). Enzymatic methods were used to assess serum lipids, glucose, and insulin concentrations. Blood pressure was measured by a sphygmomanometer and body composition with bioelectrical impedance analysis (BIA).

RESULTS

Those with a higher adherence to DRRS had a significantly higher intake of energy, fiber, and lower protein compared with those in the lower quartiles. Moreover, lower intakes of trans fats, meat, sugar sweetened beverages (SSB), and glycemic index (GI) with higher intakes of fruits, cereal fiber, polyunsaturated fatty acids/ saturated fatty acids (PUFA/ SFA) ratio, coffee, and nuts were observed in the highest versus lowest DRRS categories. Lower systolic blood pressure, diastolic blood pressure, triglyceride and, higher high-density lipoprotein values were observed in higher DRRS categories. Logistic regression analysis showed that hypertension was significantly associated with adherence to DRRS among obese individuals, the odds ratio (OR) was 0.686 (95% confidence interval [CI], 0.26-0.84) after adjustment for potential confounders. But the risk of other components of MetS was not significantly associated with higher quartiles of adherence to DRRS. Also, a non-significantly lower prevalence of MetS was observed in the higher quartile of DRRS.

CONCLUSIONS

According to the results of the current study, higher DRRS was associated with lower blood pressure, modified serum lipids, and lower Mets prevalence. Further studies in different populations are warranted for better generalization of the obtained findings.

The Serum Levels of the Heavy Metals Cu, Zn, Cd, and Pb and Progression of COPD-A Preliminary Study

There is evidence in previous studies that high levels of heavy metals may play a key role in the development of COPD due to the induction of chronic inflammation and oxidative stress. In this preliminary study, we used atomic absorption spectrophotometry to measure the levels of four heavy metals (Cu, Zn, Cd, and Pb) in blood serum of COPD patients and controls over 2 years. Clinical data on disease progression or absence were collected in patients living in the industrial region of Stara Zagora, Bulgaria. The mean values of Cu in the serum of patients with COPD and the control group were 374.29 ± 15.03 μg/L and 238.55 ± 175.31 μg/L, Zn—2010.435 ± 670.006 μg/L and 1672.78 ± 934.27 μg/L, Cd—0.334 ± 0.0216 μg/L and 0.395 ± 0.110 μg/L and Pb—0.0732 ± 0.009 μg/L and 0.075 ± 0.0153 μg/L. This is probably because these elements are biogenic and are used in the body for its anti-oxidant protection. In fact, it cannot be stated with certainty that elevated levels of Cu and Zn in the environment have a negative impact in COPD patients. There was a trend towards higher levels of the toxicants lead and cadmium in COPD patients compared to the control group of patients. There is a statistically unproven trend toward higher levels of lead and cadmium in COPD patients compared to controls, which to some extent supports our hypothesis that there is a relationship between environmental lead and cadmium levels and the COPD manifested. In COPD patients, a positive correlation was found between BMI and serum Cu levels (r = 0.413, p = 0.005). A higher concentration of serum Cu was found in men with BMI ≥ 30, compared to those with BMI < 30. There is also a positive correlation to a lesser extent between CRP and cadmium (r = 0.380; p = 0.019) and lead (r = 0.452; p = 0.004). The correlation of lead and cadmium with PSA also shows that these elements may also be associated with the presence of inflammatory processes. A significant negative correlation exists between Pb in the serum of patients with COPD and their blood hemoglobin (r = −356; p = 0.028). The results of our study suggest that higher doses of the trace elements Cu and Zn do not always have a negative effect in patients with COPD, while the toxicants Pb and Cd may be involved in COPD exacerbation and can be used as prognostic biomarkers for progression. Further studies are warranted to confirm these preliminary results.

A cross-sectional study evidences regulations of leukocytes in the colostrum of mothers with obesity

BACKGROUND

Breastmilk is a dynamic fluid whose initial function is to provide the most adapted nutrition to the neonate. Additional attributes have been recently ascribed to breastmilk, with the evidence of a specific microbiota and the presence of various components of the immune system, such as cytokines and leukocytes. The composition of breastmilk varies through time, according to the health status of mother and child, and altogether contributes to the future health of the infant. Obesity is a rising condition worldwide that creates a state of systemic, chronic inflammation including leukocytosis. Here, we asked whether colostrum, the milk produced within the first 48 h post-partum, would contain a distinct leukocyte composition depending on the body mass index (BMI) of the mother.

METHODS

We collected peripheral blood and colostrum paired samples from obese (BMI > 30) and lean (BMI < 25) mothers within 48 h post-partum and applied a panel of 6 antibodies plus a viability marker to characterize 10 major leukocyte subpopulations using flow cytometry.

RESULTS

The size, internal complexity, and surface expression of CD45 and CD16 of multiple leukocyte subpopulations were selectively regulated between blood and colostrum irrespective of the study groups, suggesting a generalized cell-specific phenotype alteration. In obesity, the colostrum B lymphocyte compartment was significantly reduced, and CD16+ blood monocytes had an increased CD16 expression compared to the lean group.

CONCLUSIONS

This is the first characterization of major leukocyte subsets in colostrum of mothers suffering from obesity and the first report of colostrum leukocyte subpopulations in Latin America. We evidence various significant alterations of most leukocyte populations between blood and colostrum and demonstrate a decreased colostrum B lymphocyte fraction in obesity. This pioneering study is a stepping stone to further investigate active immunity in human breastmilk.

Development of an Obesity Information Diagnosis Model Reflecting Body Type Information Using 3D Body Information Values

This study uses various body values (length, circumference, and volume) that can be derived from 3D data to determine variables and areas that substantially affect obesity and suggests guidelines for diagnosing obesity that are more elaborate than existing obesity indices. Body data for 170 participants (87 men and 73 women aged 20-30 years) are collected for the chest, abdomen, hips, and arms/legs. A 3D scanner, which can produce accurate body point results, and dual-energy X-ray (DEXA), which can accurately determine the fat percentage, are used to derive fat rates for each body part. The fat percentage and total fat percentage for each body part are used as learning data. For the derived data, the eigenvalue for each body part is derived using a principal component analysis, and the following four clusters are created for each part: underweight, normal, overweight, and obese. A comparison with the obesity index, which diagnoses obesity based on the cluster model, showed that the accuracy of the model proposed in this study is higher at 80%. Therefore, this model can determine the body information necessary for accurate obesity diagnosis and be used to diagnose obesity with greater accuracy than obesity indices without a body fat measurement machine such as DEXA.

Changes in Novel Anthropometric Indices of Abdominal Obesity during Weight Loss with Selected Obesity-Associated Single-Nucleotide Polymorphisms: A Small One-Year Pilot Study

Whether BMI and the competing waist circumference (WC)-based anthropometric indices are associated with obesity-related single-nucleotide polymorphisms (SNPs) is as yet unknown. The current study aimed to evaluate the anthropometric indices (fat mass index, body shape index, visceral adiposity index, relative fat mass, body roundness index, and conicity index) during a weight loss intervention in 36 obese individuals. Blood biochemical parameters (total cholesterol, low-density lipoprotein, high-density lipoprotein, and triglycerides) and three SNPs (FTO rs9939609, TFAP2B rs987237, and PLIN1 rs894160) were assessed in 22 women and 14 men (35.58 ± 9.85 years, BMI 35.04 ± 3.80 kg/m2) who completed a 12-month balanced energy-restricted diet weight loss program. Body composition was assessed via bioelectrical impedance (SECA mBCA515). At the end of the weight loss intervention, all anthropometric indices were significantly reduced (p < 0.05). For the SNP FTO rs9939609, the higher risk allele (A) was characteristic of 88.9% of the study group, in which 10 participants (27.8%) were homozygous. We found a similar distribution of alleles in TFAP2B and PLIN1. Heterozygous genotypes in FTO rs9939609 and TFAP2B rs987237 were predisposed to significant reductions in WC-based novel anthropometric indices during weight loss. The influence of PLIN1 rs894160 polymorphisms on the changes in the analyzed indices during weight loss has not been documented in the present study.

Serum uric acid is a predictive biomarker of incident metabolic syndrome at the Brazilian longitudinal study of adult Health (ELSA - Brasil)

AIM

To investigate whether serum uric acid (SUA) levels and hyperuricemia can be predictive biomarkers of incident metabolic syndrome(MS) among different body mass index(BMI) categories, and to investigate SUA cutoffs that best discriminate individuals with incident MS.

METHODS

We analyzed 7,789 participants without MS at baseline of ELSA-Brasil study. Logistic regression models were performed to evaluate associations between incident MS and SUA levels/hyperuricemia, expressed by odds ratios(ORs) and confidence intervals(95 % CI).

RESULTS

We found 1,646 incident MS cases after a median follow-up of 3.8[3.5-4.1] years. Incident MS was present among 8.3 % (n = 290) of participants with normal weight, 28.3 % (n = 850) with overweight, 39.8 % (n = 506) with obesity. Among incident MS participants of total sample, 33.0 % had hyperuricemia [SUA > 6.0 mg/dL (356.9 μmol/L)]. After all adjustments, SUA was independently prognostic of incident MS: for each 1 mg/dL increase in SUA the odds of incident MS were 45 % higher (OR1.45[CI95 %1.34-1.55 p <.01]). Associations were found for those presenting normal weight, overweight and obesity (OR1.43[CI95 %1.31-1.57 p <.01; OR1.22[CI95 %1.13-1.32 p <.01]; and OR1.16[CI95 %1.04-1.29 p <.05]) respectively. Hyperuricemia was independently associated with incident MS (OR1.88[CI95 %1.49-0.2.36 p <.01]). The SUA cut point level maximizing sensitivity and specificity in the discrimination of incident MS was 5.0 mg/dL.

CONCLUSIONS

SUA level is an independent predictive biomarker of incident MS at all BMI categories.

Normalized sensitivity of multi-dimensional body composition biomarkers for risk change prediction

The limitations of BMI as a measure of adiposity and health risks have prompted the introduction of many alternative biomarkers. However, ranking diverse biomarkers from best to worse remains challenging. This study aimed to address this issue by introducing three new approaches: (1) a calculus-derived, normalized sensitivity score (NORSE) is used to compare the predictive power of diverse adiposity biomarkers; (2) multiple biomarkers are combined into multi-dimensional models, for increased sensitivity and risk discrimination; and (3) new visualizations are introduced that convey complex statistical trends in a compact and intuitive manner. Our approach was evaluated on 23 popular biomarkers and 6 common medical conditions using a large database (National Health and Nutrition Survey, NHANES, N ~ 100,000). Our analysis established novel findings: (1) regional composition biomarkers were more predictive of risk than global ones; (2) fat-derived biomarkers had stronger predictive power than weight-related ones; (3) waist and hip are always elements of the strongest risk predictors; (4) our new, multi-dimensional biomarker models yield higher sensitivity, personalization, and separation of the negative effects of fat from the positive effects of lean mass. Our approach provides a new way to evaluate adiposity biomarkers, brings forth new important clinical insights and sets a path for future biomarker research.

DXA-Derived vs Standard Anthropometric Measures for Predicting Cardiometabolic Risk in Middle-Aged Australian Men and Women

It is not clear if dual-energy X-ray absorptiometry (DXA) adiposity measures are superior to standard anthropometric measures for predicting cardiometabolic (CM) risk factors in a middle-aged general population. In the Busselton Healthy Ageing Study, we assessed a range of standard anthropometric and DXA-derived adiposity measures to predict metabolic syndrome (MetS) and CM risk factors in 4831 "baby boomers" aged 45-69 yr. Anthropometric and whole body DXA (GE Lunar Prodigy) measures were collected. Cross-sectional relationships of overall adiposity (BMI; DXA fat mass index, body fat %), central adiposity (waist circumference (WC); DXA trunk fat, android fat, abdominal visceral adipose tissue (VAT)) and ratio index (waist-to-hip ratio; DXA trunk/legs fat, android/gynoid ratio, VAT/total fat) with MetS and its components (as both continuous and binary outcomes) were evaluated using linear and logistic regression adjusting for age and lifestyle factors. Youden's Index was used to determine the optimal cut-points for predicting MetS. In linear regression analyses, central adiposity measures showed stronger associations with MetS score and CM risk factors than overall adiposity measures and fat ratio index, and DXA-VAT provided stronger associations than WC. Logistic regression models showed similar findings. For MetS diagnosis present in 35.9% of males and 24.4% of females, the highest odds ratio (95% CI) per SD change was observed for DXA-VAT (males: 5.02 [4.28, 5.88]; females: 3.91 [3.40, 4.49]), which remained significant (all p < 0.001) after further adjustment for BMI (males: 3.27 [2.65, 4.02]; females: 3.37 [2.79, 4.06]) or WC (males: 2.46 [1.95, 3.10]; females: 2.75 [2.21, 3.43]). The optimal DXA-VAT mass cut-point for predicting MetS was 1608 grams in males and 893 grams in females. DXA-VAT was superior to standard anthropometric and other DXA-derived adiposity measures for prediction of cardiometabolic risk factors, and has clinical utility for identifying middle-aged individuals at increased risk of MetS.

Smartphone camera based assessment of adiposity: a validation study

Body composition is a key component of health in both individuals and populations, and excess adiposity is associated with an increased risk of developing chronic diseases. Body mass index (BMI) and other clinical or commercially available tools for quantifying body fat (BF) such as DXA, MRI, CT, and photonic scanners (3DPS) are often inaccurate, cost prohibitive, or cumbersome to use. The aim of the current study was to evaluate the performance of a novel automated computer vision method, visual body composition (VBC), that uses two-dimensional photographs captured via a conventional smartphone camera to estimate percentage total body fat (%BF). The VBC algorithm is based on a state-of-the-art convolutional neural network (CNN). The hypothesis is that VBC yields better accuracy than other consumer-grade fat measurements devices. 134 healthy adults ranging in age (21-76 years), sex (61.2% women), race (60.4% White; 23.9% Black), and body mass index (BMI, 18.5-51.6 kg/m2) were evaluated at two clinical sites (N = 64 at MGH, N = 70 at PBRC). Each participant had %BF measured with VBC, three consumer and two professional bioimpedance analysis (BIA) systems. The PBRC participants also had air displacement plethysmography (ADP) measured. %BF measured by dual-energy x-ray absorptiometry (DXA) was set as the reference against which all other %BF measurements were compared. To test our scientific hypothesis we run multiple, pair-wise Wilcoxon signed rank tests where we compare each competing measurement tool (VBC, BIA, …) with respect to the same ground-truth (DXA). Relative to DXA, VBC had the lowest mean absolute error and standard deviation (2.16 ± 1.54%) compared to all of the other evaluated methods (p < 0.05 for all comparisons). %BF measured by VBC also had good concordance with DXA (Lin's concordance correlation coefficient, CCC: all 0.96; women 0.93; men 0.94), whereas BMI had very poor concordance (CCC: all 0.45; women 0.40; men 0.74). Bland-Altman analysis of VBC revealed the tightest limits of agreement (LOA) and absence of significant bias relative to DXA (bias -0.42%, R2 = 0.03; p = 0.062; LOA -5.5% to +4.7%), whereas all other evaluated methods had significant (p < 0.01) bias and wider limits of agreement. Bias in Bland-Altman analyses is defined as the discordance between the y = 0 axis and the regressed line computed from the data in the plot. In this first validation study of a novel, accessible, and easy-to-use system, VBC body fat estimates were accurate and without significant bias compared to DXA as the reference; VBC performance exceeded those of all other BIA and ADP methods evaluated. The wide availability of smartphones suggests that the VBC method for evaluating %BF could play an important role in quantifying adiposity levels in a wide range of settings.Trial registration: ClinicalTrials.gov Identifier: NCT04854421.