Waist Circumference-to-Height Ratio Detected in a Convenient Sample of Young Slovak People with Increased Cardio-Metabolic Risk

Anthropometric indices and cut-off points for screening of metabolic syndrome among South African taxi drivers

Background

Detecting the early onset of metabolic syndrome (MetS) allows for quick intervention which may slow progression to a variety of health consequences, hence, determining the best measurement to detect MetS is essential.

Aim

This research aimed at examining the MetS predictive power of anthropometric indices, such as body mass index (BMI), waist circumference (WC), waist-to-height ratio (WHtR), body shape index (ABSI), body roundness index (BRI), percentage body fat (%BF), conicity index (CI), and Clínica Universidad de Navarra-body adiposity estimator (CUN-BAE) to determine the cut-off points to identify male South African taxi drivers with MetS.

Method

A cross-sectional study was conducted among 185 male taxi drivers. Their weight, height, WC, blood lipid profile were measured. International Diabetes Federation (IDF) definition was used to define MetS. Receiver Operating Characteristic (ROC) curves were used to compare the predictive ability of Anthropometric indices to detect MetS.

Results

The mean age of the participants was 39.84 years. Overall, 41.6% (N = 77) of the participants presented with MetS. The mean values for BMI, WC, WHtR, %BF, BRI, CUN-BAE, ABSI and CI were 28.60 ± 6.20 kg/m², 99.13 ± 17.59 cm, 0.58 ± 0.10, 27.28 ± 8.28%, 5.09 ± 2.33, 27.78 ± 8.34, 0.08 ± 0.01 and 1.70 ± 0.19, respectively. The mean values for these indices were significantly (p < 0.001) higher in participants with MetS. The highest area under the curve (AUC) outcomes for screening MetS were for the %BF and CUN-BAE, followed by the BMI and WHtR, and lastly the BRI. All these anthropometric indices had outstanding discriminatory powers for predicting MetS with AUCs and sensitivity values above 80%. The BMI, WHtR, %BF, BRI, and CUN-BAE, had cut-off points for detection of metS in South African men at 28.25 kg/m², 0.55, 25.29%, 4.55, and 27.10, respectively. Based on the logistic regression models abnormal BMI, WHtR, %BF, BRI, CUN-BAE, TG, FBG, systolic BP, diastolic BP and WC showed increased risk of MetS.

Conclusion

While the %BF, CUN-BAE, BMI, WC, WHtR, BRI, CI and CUN-BAE could predict MetS among South African male taxi drivers, these indices were less effective in predicting the individual MetS risk factors such as TG, BP, and FBG.

Sex Differences in Association of Elevated Blood Pressure with Variables Characterizing Cardiometabolic Risk in Young Subjects with or Without Metabolic Abnormalities

Males present higher blood pressure (BP) values, higher prevalence of elevated BP, and a different prevalence of cardiometabolic risk factors when compared with females. We assumed that the trends of risk markers across BP categories (normotension, high normal BP, and hypertension) differ in young males and females, and between subjects without metabolic abnormalities (without obesity, insulin resistance, atherogenic dyslipidemia, hyperuricemia, or microinflammation) and those presenting them. Data from 2543 subjects (48% males) aged from 16 to 23 years were analyzed. The findings showed that 15% of males and 4% of females presented high normal BP while 9% and 1%, respectively, had hypertension. In males, variables characterizing obesity status, insulin sensitivity, atherogenic dyslipidemia, uric acid, adiponectin, a soluble receptor for advanced glycation end-products, and leukocyte counts showed worsening trends across BP categories. Females presented significant trends only for obesity measures, LDL-cholesterol, and non-HDL-cholesterol. Across BP categories, trends of variables characterizing cardiometabolic risk differed among abnormalities-free and presenting males. The multivariate model selected measures of central obesity, atherogenic dyslipidemia, insulin resistance, and uric acid as significant predictors of BP in both genders, and C-reactive protein in females. Sex differences in measures of cardiovascular health in juveniles may remain undiscovered unless two sexes are analyzed separately. These differences may have implications for sex-specific disease risk in adulthood.

Cardiorespiratory Fitness, Physical Activity, Sedentary Time and Its Association with the Atherogenic Index of Plasma in Chilean Adults: Influence of the Waist Circumference to Height Ratio

Atherogenic index of plasma (AIP) is a novel biomarker related to cardiovascular disease (CVD). Cardiorespiratory fitness (CRF) and physical activity (PA) have an inverse relationship with the AIP, while sedentary time (ST) and fatness present a positive association. This study aimed to determine the combined and independent association of CRF, PA, and ST with the AIP, and additionally to establish the waist-to-height ratio (WHtR) mediation role. Data from the Chilean national health survey were used (4671 adults). A PACS (Physical Activity Cardiorespiratory Sedentary) score was created ranging from 0 to 3, indicating the number of positive recommendations met (PA, ST, and CRF). AIP was calculated (Log10 triglycerides/high-density lipoprotein-cholesterol). The combined analysis showed that compared to those with a PACS score of 0, those with a score of 1 or 2 did not present significantly reduced AIP values (adjusted by the WHtR); however, those with a score of 3 did (OR (odds ratio) = 0.50; 95% CI, 0.32 to 0.77; p < 0.001). Independent analysis showed that CRF seems to be the only variable that supports the combined result (β = -0.212; p < 0.001). Finally, the mediation analysis indicated that the WHtR mediated the association between CRF and the AIP in 34.2% of cases. Overall, only CRF had a significant and inverse association with the AIP. Nonetheless, around one-third of this beneficial relationship is affected by an elevated WHtR.

Asymptomatic Hyperuricemia Associates with Cardiometabolic Risk Indicators in Overweight/Obese but Not in Lean Adolescents

PURPOSE

In overweight/obese adolescents, asymptomatic hyperuricemia is associated with increased prevalence of metabolic syndrome, its components, and a higher cardiometabolic risk. Whether similar associations exist in lean hyperuricemic adolescents is unknown.

SUBJECTS AND METHODS

In 2424 adolescents (51.9% females) aged 16-19 years, anthropometric variables, blood pressure, uric acid, glucose, insulin, lipid profile, inflammatory markers, and renal function were determined. Continuous cardiometabolic score was calculated. Normouricemic vs hyperuricemic subjects were compared among lean and overweight/obese individuals of both sexes.

RESULTS

Females (5.4%) and males (13.3%) presented with hyperuricemia; among them 63% of females and 53% of males were lean. In both sexes, hyperuricemic lean and hyperuricemic overweight/obese adolescents displayed similar uric acid concentrations (eg, males: 455±30 vs 461±32 µmol/L, respectively, p=0.933). Lean normouricemic adolescents manifested significantly lower uric acid levels than their overweight/obese peers (eg, males: 333±46 vs 357±41 µmol/L, respectively, p<0.001). Lean normouricemic and hyperuricemic subjects presented similar cardiometabolic score (eg, males: 2.60±0.67 vs 2.64±0.60, respectively, p=0.998); among overweight/obese adolescents those with hyperuricemia displayed higher scores compared with their normouricemic counterparts (eg, males: 3.36±1.04 vs 4.21±1.65, respectively, p<0.001). A decision-tree model revealed phenotypes associated with higher uricemia, however, distribution of individuals with hyperuricemia among phenotypes was random.

CONCLUSION

In lean adolescents, hyperuricemia is not associated with cardiometabolic profile indicating an increased risk. Existence of this rather prevalent phenotype remains undetected unless lean and overweight/obese subjects are analyzed separately. Longitudinal studies are needed to elucidate the potential clinical consequences of asymptomatic hyperuricemia in lean subjects in later life.

Prevalence of lifestyle and cardiovascular risk factors in a group of medical students

OBJECTIVE

The aim of the cross-sectional study was to evaluate cardiovascular risk factors in the group of medical students with gender, overweight and obesity categorisation.

METHODS

Cross-sectional study included 364 medical students, 207 females and 157 males. We investigated anthropometric parameters, BMI, body fat percentage, WHR (waist-hip ratio), TCH (total cholesterol) and LDL-CH (LDL-cholesterol), SBP and DBP (systolic and diastolic blood pressure). The participants also completed questionnaires with socio-demographic characteristic, including smoking, unhealthy eating, self-perceived health, and physical activity status. Statistical analysis used t-test differences in arithmetic means and OR calculation with 95% CI.

RESULTS

Prevalence of increased blood pressure (> SBP/DBP 120/80 mmHg) among participants was 10.99% (SBP) and 9.07% (DBP). The results confirmed risk of "overweight + obesity" in 15.38% (using BMI evaluation) versus 18.54% cases (using body fat percentage evaluation). The results of the study confirmed statistically higher risk for males compared to females in the following parameters: SBP, DBP, BMI, body fat percentage, self-perceived health, unhealthy eating and body weight watching. "Overweight and obesity" group (BMI evaluation) confirmed all factors on statistically significant level a risky group: SBP, DBP, body fat percentage, TCH, self-perceived health, smoking, stress at university, and body weight watching. The outputs confirmed, on the other hand, low amount of clinical obesity (0.8%), clinical hypertension (BP > 140/90) 1.1%, and clinically higher cholesterol level (TCH > 5.2 mmol/l) in 8.7% participants.

CONCLUSIONS

We confirmed higher prevalence or cardiovascular risk factors among males. Also, group of "overweight and obese" students had higher frequency of cardiovascular risk factors. Border limits for risk evaluation were strong, so on clinical level we can evaluate the group of medical students as healthy. In the group of young medical students, we confirmed lower frequency of risk factors compared to the Slovak population average.