Adiposity cut-off points for cardiovascular disease and diabetes risk in the Portuguese population: The PORMETS study

Association between cardiometabolic index and infertility among American women aged 20-45 years: a cross-sectional analysis from 2013-2020 NHANES data

BACKGROUND

While metabolic syndrome and obesity are established risk factors for infertility, previous studies have neglected age-specific analyses and nonlinear associations, particularly in women aged 20-45 years, a critical demographic for fertility and metabolic health. Therefore, this study aimed to examine the nonlinear relationship between Cardiometabolic Index(CMI) and infertility risk in US women of reproductive age (20-45 years) using nationally representative the National Health and Nutrition Examination Survey(NHANES) data (2013-2020).

METHODS

Cross-sectional data from the 2013-2020 NHANES were used to analyse 3,613 women aged 20-45 years with complete CMI and infertility data. Infertility is defined as the inability to conceive after at least 12 months of regular unprotected intercourse.The CMI was calculated using waist circumference(WC), height, triglyceride(TG), and high-density lipoprotein cholesterol (HDL-C). Multivariate logistic regression analysis, supplemented by smooth curve fitting and threshold effect analysis, was used to assess the association between CMI and infertility.

RESULTS

The mean age of the subjects was (32.8 ± 7.5) years and 488 (13.51%) of them reported infertility. CMI < 0.59 were highly correlated with risk of infertility(OR = 4.47, 95%CI: 2.19-9.15, P < 0.0001), whereas CMI ≥ 0.59 was not significantly associated with the risk of infertility (OR = 1.01, 95%CI: 0.81-1.24, P = 0.9621).

CONCLUSION

Our results show a significant positive non-linear relationship between CMI and infertility risk in US women aged 20-45, with a threshold effect.

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.

A New Approach Using BMI and FMI as Predictors of Cardio-Vascular Risk Factors among Mexican Young Adults

The study aimed to identify accurate cut-off points for waist circumference (WC), body fat percentage (BF%), body mass index (BMI), fat mass index (FMI), and fat-free mass index (FFMI), and to determine their effective accuracy to predict cardiovascular risk factors (CVRFs) among Mexican young adults. A cross-sectional study was conducted among 1730 Mexican young adults. Adiposity measures and CVRFs were assessed under fasting conditions. The optimal cut-off points were assessed using the receiver operating characteristic curve (ROC). Age-adjusted odds ratios (OR) were used to assess the associations between anthropometric measurements and CVRFs. The cut-off values found, in females and males, respectively, for high WC (≥72.3 and ≥84.9), high BF% (≥30 and ≥22.6), high BMI (≥23.7 and ≥24.4), high FMI (≥7.1 and ≥5.5), and low FFMI (≤16 and ≤18.9) differ from those set by current guidelines. High BMI in women, and high FMI in men, assessed by the 50th percentile, had the best discriminatory power in detecting CVRFs, especially high triglycerides (OR: 3.07, CI: 2.21-4.27 and OR: 3.05, CI: 2.28-4.08, respectively). Therefore, these results suggest that BMI and FMI measures should be used to improve the screening of CVRFs in Mexican young adults.

Performance of Body Fat Percentage, Fat Mass Index and Body Mass Index for Detecting Cardiometabolic Outcomes in Brazilian Adults

Obesity is a recognized risk factor for the development of cardiometabolic outcomes. Therefore, it is essential to evaluate anthropometric and body composition indicators used for its diagnosis. This study aimed to assess the diagnostic performance of body fat percentage (BF%), fat mass index (FMI) and body mass index (BMI) for detecting cardiometabolic outcomes in adults. A cross-sectional study was conducted involving adults at 30 years of age from Pelotas, RS (n = 3517) and at 37-39 years from Ribeirão Preto, SP (n = 1696). Receiver operating characteristic (ROC) curves were used to determine the cut-off points for predicting cardiometabolic risk factors, including altered blood pressure, blood glucose, triglycerides, total cholesterol, low-density lipoprotein cholesterol (LDL-c), high-density lipoprotein cholesterol (HDDL-c), C-reactive protein and glycated hemoglobin. The cut-off points of BF% ranged from 25.2 to 27.8 in men and from 37.4 to 39.7 in women at 30 years, and from 26.1 to 27.8 in men and from 38.5 to 42.2 in women at 37-39 years. For FMI (kg/m2), the cut-off points ranged from 6.3 to 7.5 in men and from 9.5 to 10.8 in women at 30 years, and from 7.3 to 7.8 in men and from 10.2 to 12.2 in women at 37-39 years. The BMI cut-off points (kg/m2) ranged from 26.3 to 27.3 in men and from 25.4 to 27.2 in women at 30 years, and from 28.3 to 29.0 in men and from 27.2 to 29.6 in women at 37-39 years. The areas under the curve were similar for the three indicators, ranging from 0.523 to 0.746. BMI showed a performance similar to that of the body fat-based indicators in identifying cardiometabolic outcomes. The cut-off points of the three indicators showed acceptable discriminatory power in subjects with cardiometabolic risk factors.

Structural Equation Modelling for Predicting the Relative Contribution of Each Component in the Metabolic Syndrome Status Change

Understanding the factor weighting in the development of metabolic syndrome (MetS) may help to predict the progression for cardiovascular and metabolic diseases. Thus, the aim of this study was to develop a confirmatory model to describe and explain the direct and indirect effect of each component in MetS status change. A total of 3581 individuals diagnosed with MetS, aged 18−102 years, were selected between January 2019 and December 2020 from a community-representative sample of Portuguese adults in a north-eastern Portuguese region to test the model’s goodness of fit. A structural equation modelling (SEM) approach and a two-way ANOVA (age × body composition) were performed to compare the relative contribution of each MetS component using joint interim statement (JIS). Waist circumference (β = 0.189−0.373, p < 0.001), fasting glucose (β = 0.168−0.199, p < 0.001) and systolic blood pressure (β = 0.140−0.162, p < 0.001) had the highest direct effect on the change in MetS status in the overall population and concerning both sexes. Moreover, diastolic blood pressure (DBP), triglycerides (TG) and high-density lipoprotein cholesterol (HDL-c) had a low or non-significant effect. Additionally, an indirect effect was reported for age and body composition involving the change in MetS status. The findings may suggest that other components with higher specificity and sensitivity should be considered to empirically validate the harmonised definition of MetS. Current research provides the first multivariate model for predicting the relative contribution of each component in the MetS status change, specifically in Portuguese adults.

Cutoff points of adiposity anthropometric indices for low muscle mass screening in middle-aged and older healthy women

Background

The reduction of female sex hormones causes changes in the contractile properties of muscles as well as infiltration of fat in the muscle tissue. This results in a consequent decline in muscle strength. These changes are related to higher levels of functional impairment and physical disability. In this sense, several anthropometric indices have been used to quantify body and visceral fat. Thus, the objective of this paper is to propose cutoff points for adiposity anthropometric indices in order to identify low muscle mass, as well as to analyze the relationship between these indices and low muscle mass in middle-aged and older women.

Methods

Cross-sectional analytical study carried out in the Northeast of Brazil. The sample was formed by 593 women between 40—80 years old. Data collection included anthropometric assessment (BMI: Body Mass Index – WC: Waist Circumference – WHR: Waist-to-hip Ratio – WHtR: Waist-to-height Ratio – CI: Conicity Index – BAI: Body Adiposity Index – VAI: Visceral Adiposity Index – LAP: Lipid Accumulation Product), bioimpedance test and biochemical dosage. Moreover, sociodemographic data and practice of physical activity were collected. Descriptive statistics, Student's t-test, ROC curves, chi-squared and logistic regression were performed.

Results

The participants had a mean age of 53.11 (8.89) years, BMI of 28.49 (5.17) kg/m² and WC of 95.35 (10.39). The prevalence of low muscle mass was 19.4%. Based on sensitivity and specificity of adiposity anthropometric indices, cutoff points were developed to identify the presence of low muscle mass (p < 0.05), except for VAI. After logistic regression, WC (OR = 6.2; CI 95%: 1.4—28.1), WHR (OR = 1.8; CI: 1.0—3.4), WHtR (OR = 5.0; CI 95%: 1.0—23.7) and BAI (OR = 14.5; CI 95%: 6.6—31.7) were associated with low muscle mass.

Conclusions

All anthropometric indices, except VAI, showed adequate accuracy in identifying low muscle mass in women, especially those that took into account WC. This suggests that they can become accessible and also be cost-effective strategies for assessing and managing health outcomes related to muscle mass analysis.

Optimal waist circumference cutoff values to predict cardiometabolic alterations in a Venezuela national representative sample. The EVESCAM study

BACKGROUND

Waist circumference (WC) value reflects abdominal adiposity, but the amount abdominal fat that is associated to cardiometabolic risk factors varies among ethnicities. Determination of metabolic abnormalities has not undergone a WC adaptation process in Venezuela.

AIMS

The aim of the study was (1) to determine the optimal WC cutoff value associated with ≥2 cardiometabolic alterations and (2) incorporating this new WC cutoff, to determine the prevalence of abdominal obesity and cardiometabolic risk factors related in Venezuela.

METHODS

The study was national population-based, cross-sectional, and randomized sample, from 2014 to 2017. To assess performance of WC for identifying cardiometabolic alterations, receiver operating characteristics curves, area under the curve (AUC), sensitivity, specificity, and positive likelihood ratios were calculated.

RESULTS

Three thousand three hundred eighty-seven adults were evaluated with mean age of 41.2 ± 15.8 years. Using the best tradeoff between sensitivity and specificity, WC cutoffs of 90 cm in men (sensitivity = 72.4% and specificity = 66.1%) and 86 cm in women (sensitivity = 76.2% and specificity = 61.4%) were optimal for aggregation of ≥2 cardiometabolic alterations. AUC was 0.75 in men and 0.73 in women using these new cutoffs. Prevalence of abdominal obesity and metabolic syndrome was 59.6% (95 CI; 57.5-61.7) and 47.6% (95 CI; 45.2-50.0), respectively. Cardiometabolic risk factors were associated with being men, higher age, adiposity, and living in northern or western regions.

CONCLUSION

The optimal WC values associated with cardiometabolic alterations were 90 cm in men and 86 cm in women. More than half of the Venezuelan population had abdominal obesity incorporating this new WC cutoff.

Altitude and its inverse association with abdominal obesity in an Andean country: a cross-sectional study

Background: Abdominal obesity represents an accurate predictor of overall morbidity and mortality, which is worrisome because it is also continuously increasing across Andean countries. However, its relationship with altitude remains unclear. The objective of this study was to assess the association between altitude and abdominal obesity in Peru, and how sociodemographic variables impact this association. Methods: We estimated the prevalence of abdominal obesity in Peru and analyzed its association with altitude using the data from the 2012-2013 National Household Survey (ENAHO). During this survey, a representative sample of Peruvians was screened for abdominal obesity, using waist circumference as a proxy, and the Adult Treatment Panel III guidelines cutoffs. Results: Data were analyzed from a sample of 20,489 Peruvians (51% male). The prevalence of abdominal obesity was estimated at 33.6% (95% CI: 32.5 to 34.6%). In Peru, altitude was significantly and inversely associated with abdominal obesity, decreasing with higher altitudes: 1500-2999 meters above mean sea level (MAMSL) vs <1500 MAMSL, adjusted prevalence rate [aPR]= 0.86 (95% CI: 0.75 to 0.97); ≥3000 MAMSL vs <1500 MAMSL, aPR= 0.98 (95% CI: 0.87 to 1.11), when adjusting by age, gender and residence area (rural/urban). However, this association was significantly modified by age and gender ( p< 0.001). Conclusion: Abdominal obesity is highly prevalent in Peru and decreases significantly with altitude, but age and gender modify this association. Thus, abdominal obesity appears to affect older women from low altitudes more than younger men from high altitudes.

Association between body adiposity index and coronary risk in the Brazilian Longitudinal Study of Adult Health (ELSA-Brasil)

BACKGROUND & AIMS

The body adiposity index (BAI) was recently proposed as a better indicator of body adiposity than body mass index in adults. The association between BAI and cardiometabolic risk factors has been widely investigated. However, the strength and magnitude of these associations varied as a function of the endpoint evaluated, the study design, the population investigated, and the cut-off points used. The aim of this study was to investigate the association between BAI and coronary heart disease (CHD) risk in a large sample of Brazilian adults and to propose the most appropriate cut-off points for BAI for the identification of CHD risk in the adult Brazilian population.

METHODS

Data from 15,092 civil servants (54.4% women) from universities and research institutes in six Brazilian states were evaluated in the Brazilian Longitudinal Study of Adult Health (ELSA-Brasil). All were aged 35-74 years at baseline. The Framingham coronary risk score was used to identify a very high risk of CHD (≥20% risk of CHD over the next 10 years) and a high risk of CHD (≥10% risk). BAI cut-off points capable of detecting a risk of CHD were determined using ROC curves and associations were tested using Poisson regression with robust variance, according to sex and age. Three multivariable models were examined.

RESULTS

BAI remained positively associated with a very high and high risk of CHD following adjustment for potential confounding factors in all the strata and multivariable models (p < 0.05), with the exception of model 3 (adjusted for education level and waist-to-hip ratio) for very a high risk of CHD in younger women (p = 0.06). In the adjusted models, the prevalence ratios for a very high and high risk of CHD, irrespective of age group, varied between 1.23 (95%CI: 1.09-1.39) and 1.64 (1.33-2.03) and 1.07 (1.03-1.12) and 1.47 (1.36-1.60) in men; and 1.57 (1.08-2.31) and 2.42 (1.36-4.31) and 1.29 (1.13-1.47) and 1.82 (1.54-2.15) in women, respectively. The optimal cut-off points of BAI to determine a risk of CHD were: 28.0 in men of both age groups, and 34.0 in younger women and 36.0 in older women to determine a very high risk; and 26.0 in younger men and 34.0 in women of both age groups to determine a high risk. BAI showed a reasonable ability to predict coronary risk in participants of the ELSA-Brasil (AUC>60%, except for the group of men of 60-74 years of age).

CONCLUSIONS

Higher BAI levels were found to be associated with a greater risk of developing CHD in both men and women of different ages participating in the ELSA-Brasil, suggesting that BAI may be a useful tool for screening for CHD risk in Brazilian adults.

Visceral Obesity and Metabolic Syndrome Are Associated with Well-Differentiated Gastroenteropancreatic Neuroendocrine Tumors

The determinants for gastroenteropancreatic neuroendocrine tumors (GEP-NET) recent burden are matters of debate. Obesity and metabolic syndrome (MetS) are well established risks for several cancers even though no link with GEP-NETs was yet established. Our aim in this study was to investigate whether well-differentiated GEP-NETs were associated with obesity and MetS. Patients with well-differentiated GEP-NETs (n = 96) were cross-matched for age, gender, and district of residence with a control group (n = 96) derived from the general population in a case-control study. Patients presented gastro-intestinal (75.0%) or pancreatic (22.9%) tumors, grade G1 (66.7%) or G2 (27.1%) with localized disease (31.3%), regional metastasis (16.7%) or distant metastasis (43.8%) at diagnosis, and 45.8% had clinical hormonal syndromes. MetS was defined according to Joint Interim Statement (JIS) criteria. Well-differentiated GEP-NETs were associated with MetS criteria as well as the individual components' waist circumference, fasting triglycerides, and fasting plasma glucose (p = 0.003, p = 0.002, p = 0.011 and p < 0.001, respectively). The likelihood of the association was higher when the number of individual MetS components was greater than four. MetS and some individual MetS components including visceral obesity, dyslipidemia, and increased fasting glucose are associated with well-differentiated GEP-NET. This data provides a novel insight in unraveling the mechanisms leading to GEP-NET disease.