Predictors Of Metabolic Syndrome Research Articles

Neck Circumference as a Predictor of Metabolic Syndrome in Koreans: A Cross-Sectional Study.

Metabolic syndrome (MetS) is a complex metabolic disorder and a high-risk condition for type 2 diabetes and cardiovascular disease. Rapid screening of at-risk individuals using accurate and time-saving tools is effective in disease management. Using the Korea National Health and Nutrition Examination Survey (KNHANES) data, we collected data from 2234 participants suitable for the study design, of which 974 (43.6%) were men and 1260 (56.4%) were women. We used receiver operating characteristic (ROC) curve analysis to estimate the optimal sex-specific neck circumference (NC) cut-off point to predict the MetS risk. To analyze the risk of MetS according to the estimated NC, logistic regression analysis was performed to identify the confounding factors. The result of the ROC analysis showed that the optimal neck cut-off points for predicting the risk of MetS were 38.25 cm (AUC: 0.759, 95% CI: 0.729–0.790) in men and 33.65 cm (AUC: 0.811, 95% CI: 0.782–0.840) in women. In the upper NC cut-off point compared to the lower NC cut-off point, NC was associated with an increased MetS risk by 2.014-fold (p = 0.010) in men and 3.650-fold (p < 0.001) in women, after adjustments. The current study supports NC as an effective anthropometric indicator for predicting the risk of MetS. It is suggested that more studies should be conducted to analyze the disease prediction effect of the combined application of anthropometric indicators currently in use and NC.

Levels of Interleukin 6 as a Predictor of Metabolic Syndrome in Schizophrenic Patients Receiving Combination Therapy of Typical and Atypical Antipsychotics

BACKGROUND: Schizophrenia is a severe psychiatric disorder that causes disability and is often accompanied by physical illness. Based on the American Heart Association criteria, metabolic syndrome is common in schizophrenic patients, with a prevalence of 43% in Clinical Antipsychotic Trials of Intervention Effectiveness. The metabolic syndrome in patients with schizophrenia results from the side effects of antipsychotics. The metabolic syndrome will also show high levels of IL-6. This situation can have biological implications, which can then affect the health of schizophrenic patients. AIM: This study aims to determine serum IL-6 levels as a predictor of metabolic syndrome in patients with metabolic syndrome due to side effects of using antipsychotic therapy. METHODS: This prospective cohort study was not randomized, with the number of subjects was 28 schizophrenic patients who were evenly divided into two groups, namely, the group receiving atypical and typical combination therapy. Therapy was given to both groups for 3 months, and measurements and checks of bodyweight, abdominal circumference, blood pressure, BMI, TG, GDP, and Il-6 levels were carried out at baseline and 3rd month. Comparative and correlation tests were carried out between groups. RESULTS: Some schizophrenic patients were categorized as metabolic syndrome and not a metabolic syndrome in both therapy groups (p &lt; 0.020). However, atypical antipsychotic drug combinations are more likely to experience the metabolic syndrome. There was a change in the mean Il-6 levels at baseline and the 3rd month in both groups (p &lt; 0.0001). There was a more excellent mean value of IL-6 levels at 3rd month with metabolic syndrome than those without metabolic syndrome. There was a greater mean value of IL-6 levels at third month with metabolic syndrome compared with those without metabolic syndrome in the haloperidol and chlorpromazine groups (p &lt;0.005), the risperidone and clozapine groups (p &lt;0.002). CONCLUSION: Metabolic syndrome is more common in schizophrenic patients receiving atypical than typical combination therapy. The body’s response to the metabolic syndrome results in an increase in IL-6 levels due to an inflammatory process in visceral fat which accumulates due to weight gain due to the administration of antipsychotics. In schizophrenic patients with metabolic syndrome, IL-6 levels are higher than those without metabolic syndrome, so that IL-6 levels can be used as a predictor of metabolic syndrome in schizophrenic patients receiving antipsychotic therapy.

Eating Speed, Physical Activity, and Cardiorespiratory Fitness Are Independent Predictors of Metabolic Syndrome in Korean University Students.

Background: Little is known regarding the role of eating quickly, physical inactivity, and poor cardiorespiratory fitness (CRF) in assessing the onset of metabolic syndrome (Mets) in Korean young adults. Objectives: This study examined the association between the three risk factors and Mets in 1891 Korean university students (30% female) aged 18–29 years. Methods: Eating speed (slow vs. fast) and physical activity (active vs. inactive) were assessed with a standardized questionnaire. Maximal oxygen uptake as an indicator of CRF was assessed with graded exercise testing. Components of Mets were waist circumference, systolic and diastolic blood pressures, fasting blood glucose (FBG), triglycerides (TG), and high-density lipoprotein cholesterol (HDLC). Results: All the three exposures were positively associated with abdominal obesity, elevated blood pressures, elevated FBG, elevated TG, and decreased HDLC. Logistic regression analysis showed that the odds ratio (OR) of Mets was incremental in the order of physical inactivity (odds ratio, OR = 1.666; 95% confidence interval, CI = 1.024–2.708; p = 0.040), fast eating (OR = 1.687; 95% CI = 1.094–2.601; p = 0.018), and poor CRF (OR = 5.378; 95% CI = 3.475–8.325; p < 0.001). Conclusions: The current findings suggest that a multifaceted intervention targeting at promotion of physical activity and CRF in concert with healthy eating behaviors should be implemented as a preventive strategy against Mets in Korean university students.

Body impedance analyzer and anthropometric indicators; predictors of metabolic syndrome.

AimMetabolic syndrome is one of the outcomes of a sedentary lifestyle in the modern world. In this study, we want to introduce the predictors of metabolic syndrome using anthropometric indices and Bio-Electrical Impedance Analysis (BIA) test values.MethodThis cross-sectional study was performed on 2284 employees of Tehran University of Medical Sciences in different job categories. Metabolic syndrome was determined according to IDF criteria. Anthropometric dimensions, para-clinical tests, basic information were collected from the participants. Also, the body analysis of the participants was performed using a BIA method.ResultThe prevalence of metabolic syndrome in this study was 23.2% based on IDF criteria, which was 21% and 26.6% in men and women, respectively. The most important factor among the components of IDF criteria was HDL deficiency. In this study, neck circumference, fat mass, visceral fat, muscle mass percentage and waist to height ratio were observed as predictors of metabolic syndrome.ConclusionThis study realized that there is association between fat mass, fat-free mass, visceral fat and muscle mass which all are some elements of body composition analysis and metabolic syndrome as a major health issue.

Magnitude, components and predictors of metabolic syndrome in Northern Ethiopia: Evidences from regional NCDs STEPS survey, 2016.

Individuals with metabolic syndrome are five times more susceptible to chronic diseases. Assessment of its magnitude, components, and risk factors is essentials to deploy visible interventions needed to avoid further complications. The study aimed to assess magnitude, components, and predictors of metabolic syndrome in Tigray region northern Ethiopia, 2016. Data were reviewed from Tigray region NCDs STEPs survey data base between May to June 2016. A total of 1476 adults aged 18-64 years were enrolled for the study. Multi-variable regression analysis was performed to estimate the net effect of size to risk factors associated with metabolic syndrome. Statistical significance was declared at p-value of ≤0.05 at 95% confidence interval (CI) for an adjusted odds ratio (AOR). The study revealed that unadjusted and adjusted prevalence rate of Metabolic Syndrome (MetS) were (CPR = 33.79%; 95%CI: 31.29%-36.36%) and (APR = 34.2%; 95% CI: 30.31%-38.06%) respectively. The most prevalent MetS component was low HDL concentration (CPR = 70.91%; 95%CI: 68.47%-73.27%) and (APR = 70.61; 95%CI; 67.17-74.05). While; high fasting blood glucose (CPR = 20.01% (95%CI: 18.03-22.12) and (APR = 21.72; 95%CI; 18.41-25.03) was the least ones. Eating vegetables four days a week, (AOR = 3.69, 95%CI; 1.33-10.22), a salt sauce added in the food some times (AOR = 5.06, 95%CI; 2.07-12.34), overweight (AOR = 24.28, 95%CI; 10.08-58.47] and obesity (AOR = 38.81; 12.20-111.04) had strong association with MetS. The magnitude of metabolic syndrome was found to be close to the national estimate. Community awareness on life style modification based on identified MetS components and risk factors is needed to avoid further complications.

Prevalence and Predictors of Metabolic Syndrome among Patients with Bronchial Asthma: A Cross Sectional Study

Background:Recent studies have reported the epidemiological link between Metabolic Syndrome (MS) and asthma, but it has rarely been studied in Egypt. The study aimed to investigate the prevalence of MS and its predictors among asthma patients in Egypt.Methods:In total, 320 patients with bronchial asthma were included. The following were assessed: spirometric evaluation, anthropometric indices, blood pressure, fasting blood sugar and serum lipid profile. We analyzed the correlation between metabolic scores and patient characteristics. Predictors of MS were identified using logistic regression analysis.Results:The prevalence of MS was 57.5% in asthma patients. For asthma patients, low High-Density Lipoprotein (HDL) and abdominal obesity were the commonest metabolic abnormality. Waist circumference, Fasting Blood Sugar (FBS) and triglyceride correlated significantly with asthma (P ‹ 0.05). FBS and DBP were the best predictors of MS.Conclusion:MS is frequent in asthma patients in Egypt. Obesity and lipid abnormalities were the commonest metabolic abnormality. Screening of these patients for components of metabolic syndrome should be a part of routine workup.

Metabolic Syndrome Prevalence and Cardiovascular Risk Assessment in HIV-Positive Men with and without Antiretroviral Therapy.

Treatment of HIV infection is a lifelong process and associated with chronic diseases. We evaluated the prevalence and predictors of metabolic syndrome (MetS) and cardiovascular diseases (CVDs) with individual antiretroviral drugs exposure among HIV-infected men in Taiwan. A total of 200 patients’ data were collected with a mean age of 32.9. Among them, those who had CD4 positive cell number less than 350/mL were eligible to have highly active antiretroviral therapy (HAART). Patients were divided into group-1 that contains 45 treatment-naïve participants, and group-2 that includes 155 HAART treatment-experienced participants. MetS prevalence between group-1 and group-2 was 18% and 31%, respectively. The Framingham Risk Score (FRS) for the naïve and experienced groups were 4.7 ± 4.2 and 3.87 ± 5.92, respectively. High triglyceride (TG > 150 mg/dL) in group-1 and group-2 were 15.6% and 36.6% (p < 0.05), whereas, lower high-density lipoprotein (HDL < 39 mg/dL) in group-1 and group-2 presented as 76.7% versus 51% (p < 0.05), respectively. In group-2, treatment with protease inhibitors (PIs) resulted in higher TG levels when compared with non-nucleotide reverse transcriptase inhibitors (NNRTIs) and integrase inhibitors (InSTIs). The prevalence of MetS in the treatment-naïve group was lower than that of the treatment-experienced group; high TG level resulted in higher MetS prevalence in the treatment-experienced group. In contrast, the cardiovascular risk of FRS in the treatment-naïve group was higher than that of the treatment-experienced group, which may result from the low HDL level. Although group-1 participants have a higher risk of developing CVDs, in group-2, an increasing TG level in PIs user indicated higher CVDs risk. TG and HDL are two significant biofactors that required regular evaluation in HIV-positive individuals.

Comparison of the triglyceride glucose index and blood leukocyte indices as predictors of metabolic syndrome in healthy Chinese population

Triglyceride glucose (TyG) index and inflammatory markers are reported to have a positive association with metabolic syndrome (MetS). However, no previous study has assessed the value of TyG index and inflammatory markers as predictors of metabolic syndrome in the same study. This study looks at the comparison of the triglyceride index and blood leukocyte indices as predictors of metabolic syndrome in the Chinese population. The study cohort involved 1542 Chinese population without metabolic syndrome. The subjects underwent comprehensive routine health examination in 2011 and returned for a follow-up examination in 2016. Metabolic syndrome was defined according to Chinese Diabetes Society criteria, using body mass index for the replacement of waist circumference. TyG index, total leukocytes, neutrophils, lymphocytes, and neutrophil-to-lymphocyte ratio (NLR) were measured. Adjust d logistic models were used to assess the relationship between TyG index, blood leukocyte indices, and incident MetS. Receiver operating characteristic (ROC) curves were performed to determine the predictive value of TyG index and blood leukocyte indices for MetS. Results from multivariate logistic regression analysis showed that, in the adjusted model, the subjects with the highest quartile of TyG index and neutrophils had a 3.894- and 1.663-fold increased incidence of MetS (P < 0.0001 and P = 0.027), respectively. No significant association was observed between total leukocytes, lymphocytes, NLR with incident MetS. ROC analysis showed that the AUC of TyG index and neutrophils were 0.674 and 0.568 for incident MetS, respectively. TyG index rather than blood leukocyte indices may have the strongest predictive value in MetS development over a 5-year period.

Atherogenic index of plasma as predictors for metabolic syndrome, hypertension and diabetes mellitus in Taiwan citizens: a 9-year longitudinal study

Deeply involved with dyslipidemia, cardiovascular disease has becoming the leading cause of mortality since the early twentieth century in the modern world. Whose correlation with metabolic syndrome (MetS), hypertension and type 2 diabetes mellitus (T2DM) has been well established. We conducted a 9-year longitudinal study to identify the association between easily measured lipid parameters, future MetS, hypertension and T2DM by gender and age distribution. Divided into three groups by age (young age: < 40, middle age: ≥ 40 and < 65 and old age: ≥ 65), 7670 participants, receiving standard medical inspection at Tri-Service General Hospital (TSGH) in Taiwan, had been enrolled in this study. Atherogenic index of plasma (AIP) was a logarithmically transformed ratio of triglyceride (TG)/high-density lipoprotein cholesterol (HDL-C). Through multivariate regression analyses, the hazard ratio (HR) of AIP for MetS, hypertension and T2DM were illustrated. AIP revealed significant association with all the aforementioned diseases through the entire three models for both genders. Additionally, AIP revealed significant correlation which remained still after fully adjustment in MetS, hypertension, and T2DM groups for subjects aged 40–64-year-old. Nevertheless, for participants aged above 65-year-old, AIP only demonstrated significant association in MetS group. Our results explore the promising value of AIP to determine the high-risk subjects, especially meddle-aged ones, having MetS, hypertension, and T2DM in the present and the future.

Understanding the role of oxidative stress in the incidence of metabolic syndrome and obstructive sleep apnea

BackgroundUnderstanding the causes and risk factors of metabolic syndrome is important for promoting population health. Oxidative stress has been associated with metabolic syndrome, and also obstructive sleep apnea. These are two diseases which have common prognostic characteristics for heart disease. The aim of this study was to examine the role of oxidative stress in the concurrent presence of metabolic syndrome and obstructive sleep apnea in a working population.MethodsParticipants were 163 artisan bakers in Shahroud, Iran, routinely exposed to significant heat stress and other oxidative stress indicators on a daily basis as part of their work. Using a cross-sectional design, data relevant to determining metabolic syndrome status according to International Diabetes Federation criteria, and the presence of obstructive sleep apnea according to the STOP-Bang score, was collected. Analyses included hierarchical binary logistic regression to yield predictors of the two diseases.ResultsHierarchical binary logistic regression showed that oxidative stress – alongside obesity, no regular exercise, and smoking – was an independent predictor of metabolic syndrome, but not obstructive sleep apnea. Participants who were obese were 28 times more likely to have metabolic syndrome (OR 28.59, 95% CI 4.91–63.02) and 44 times more likely to have obstructive sleep apnea (OR 44.48, 95% CI 4.91–403.28). Participants meeting metabolic syndrome criteria had significantly higher levels of malondialdehyde (p < 0.05) than those who did not. No difference in oxidative stress index levels were found according to obstructive sleep apnea status.ConclusionsOur findings suggest that oxidative stress contributes to the onset of metabolic syndrome, and that obstructive sleep apnea is involved in oxidative stress. Whilst obesity, exercise, and smoking remain important targets for reducing the incidence of metabolic syndrome and obstructive sleep apnea, policies to control risks of prolonged exposure to oxidative stress are also relevant in occupations where such environmental conditions exist.

Investigation of the Association between Smoking Behavior and Metabolic Syndrome Using Lipid Accumulation Product Index among South Korean Adults.

Electronic cigarette vaping has recently been chosen as a smoking alternative for those who want to quit smoking, but some of the electronic cigarette users use both traditional and electronic cigarettes (dual smoking) without stopping smoking. This study investigated the association between smoking behavior and metabolic syndrome among Korean adults. Data from 14,607 participants (6142 males and 8465 females) were examined. They were divided into four categories: dual smoking (both conventional and e-cigarettes), single smoking (only conventional cigarettes), previously smoking, and non-smoking. Metabolic syndrome risk was calculated as a continuous variable using the lipid accumulation product (LAP) index. Multiple linear regression analyses were performed to examine the association of log-transformed LAP with smoking behavior. Among the total participants, 187 males and 35 females were dual smokers and 1850 males and 372 females were single smokers. LAP was significantly higher in male who practiced dual and single smoking than LAP of non-smokers—dual: β = 0.27, standard error (SE) = 0.06, p < 0.0001; single: β = 0.18, SE = 0.03, p < 0.0001. In female, LAP was significantly higher among those who practiced only single smoking than LAP of non-smokers (β = 0.21, SE = 0.04, p < 0.0001). Dual and single smoking were significantly associated with higher LAP, a strong predictor of metabolic syndrome. Further studies and awareness regarding the adverse effects of dual smoking are required.

Predictors of Metabolic Syndrome in Adults and Older Adults from Amazonas, Brazil.

Metabolic syndrome has been considered a factor of vulnerability and a major public health problem because it increases the risk of cardiovascular disease and type 2 diabetes. The present study from Amazonas, Brazil aimed to estimate the prevalence of the individual and general components of metabolic syndrome in adults and older adults and identify the independent predictors of metabolic syndrome. The sample of the present cross-sectional study comprised 942 participants (590 women), with a mean age of 59.8 ± 19.7 (range: 17.5 to 91.8). Blood pressure in men (62.5%), abdominal obesity in women (67.3%), and lower high-density lipoprotein cholesterol (HDL-C) in both (52.2% in men and 65.0% in women) were the most prevalent individual risk factors for metabolic syndrome. Women had a higher prevalence of abdominal obesity (p < 0.001), low HDL-C (p < 0.001), and metabolic syndrome (p < 0.001) than men; however, opposite results were seen in men for blood pressure (p < 0.001). The overall prevalence of metabolic syndrome was 47.5%. Advanced age, being female, having a higher body mass index, and a having lower educational level independently increased the odds of metabolic syndrome. Due to the association of metabolic syndrome with deterioration of health status and increased vulnerability, this study sustains the need for early public health interventions in the Amazonas region.

Triglyceride‐To‐High-Density-Lipoprotein-Cholesterol Ratio as a Predictor for Metabolic Syndrome According to Obesity Onset in Women With Severe Obesity

Triglyceride‐To‐High-Density-Lipoprotein-Cholesterol Ratio as a Predictor for Metabolic Syndrome According to Obesity Onset in Women With Severe Obesity

Prevalence and correlates of metabolic syndrome and its components in adults with psychotic disorders in Eldoret, Kenya.

A high prevalence of metabolic syndrome and its components in patients with psychotic disorders may increase the risk for cardiovascular diseases. Unfortunately, relatively little work in this field has emerged from low-resourced contexts. This study investigated the prevalence, correlates, and treatment patterns of metabolic disorders in patients with psychotic disorders in Western Kenya. 300 patients with psychosis and 300 controls were recruited at Moi Teaching and Referral Hospital in Eldoret, Kenya. Data on demographic characteristics, weight, height, abdominal circumference, blood pressure, blood glucose, lipid profile, and treatments were collected. Categorical and continuous data were compared between the patient and control groups using Pearson's chi-squared tests and t-tests, respectively. Variables found to be significantly different between these groups were included in logistic regression models to determine potential predictors of metabolic syndrome. Compared to controls, patients with psychosis were found to have a higher mean random blood glucose [5.23 vs 4.79, p = 0.003], higher body mass index [5.23 vs 4.79, p = 0.001], higher triglycerides [1.98 vs 1.56, p<0.001], larger waist circumference [89.23 vs 86.39, p = 0.009] and lower high density lipoprotein [1.22 vs 1.32, p<0.001]. The odds of developing metabolic syndrome were increased with age [OR = 1.05, CI: 1.02-1.07] and presence of a psychotic disorder [OR = 2.09 [CI 1.23-3.55]; and were reduced with female gender [OR 0.41, CI 0.25-0.67], among those who were never married [OR 0.52, CI 0.28-0.94] and among the widowed/separated/ divorced marital status [OR 0.38, CI 0.17-0.81]. While the majority of patients received treatment with olanzapine, there was no association between olanzapine use and metabolic syndrome and its components. More than half of the patients in this study sample were not receiving treatment for the various components of metabolic syndrome. In the study setting of Eldoret, metabolic syndrome and its components were more prevalent among patients with psychotic disorders than in controls; and a clear treatment gap for these disorders was evident. There is a need for efforts to ensure adequate screening and treatment for these physical disorders in resource-limited settings.

Triglycerides/high-density lipoprotein-cholesterol ratio in children with metabolic syndrome

ABSTRACT The incidence of metabolic syndrome in children is increasing due to the obesity epidemic. Accessible biochemical studies are required to diagnose and treat it in a timely manner. This cross-sectional study aims to assess the usefulness of the triglycerides/high-density lipoprotein-cholesterol (TG/HDL-c) index as a predictor of metabolic syndrome according to the diagnostic criteria of the European initiative Identification and prevention of Dietary- and lifestyle-induced health EFects In Children and infantS (IDEFICS) in obese children 3 to 10 years of age. Descriptive, observational, retrospective study in the pediatric service of León General Hospital, Guanajuato, México, from January 2017 to December 2018. In a group of 73 obese children aged 3 to 10 years, it was found that the TG/HDL-c ratio has an odds ratio of 6 (95% CI 2–18) as a predictor of metabolic syndrome. A cut-off point of 2.4 for this index has a sensitivity of 85%, specificity of 85%, likelihood ratio of 5.6, positive predictive value of 94%, and negative predictive value of 68% to diagnose metabolic syndrome with IDEFICS criteria. The TG/HDL-c index is a useful indicator to diagnose metabolic syndrome in children 3 to 10 years of age with obesity, in whom it is not possible to perform a comprehensive biochemical study.

Prevalence of Metabolic Syndrome and its Components in Kanifing Municipality, The Gambia.

Background:Metabolic syndrome (MetS) is a complex syndrome with clustering of interrelated risk factors for cardiovascular disease and diabetes. Its rising worldwide prevalence has been largely related to the increasing obesity. In The Gambia, the last and only time a MetS related study was conducted, and then reported, was 21 years. Therefore, there is need for evaluating the prevalence of MetS and its components in the country.Objective:This study was aimed to evaluate the prevalence of MetS and its individual components in Kanifing Municipality (KM).Methods:It was a cross-sectional study conducted at Kanifing General Hospital, Kanifing Municipality. Data obtained from each participants included anthropometric indices, blood pressure, fasting plasma glucose, triglyceride and high-density lipoprotein levels, and clinical information.Results:One hundred and thirty-six participants were included in the analysis. The overall MetS prevalence was 54.4% with significant female predominance (female, 58%; male, 29.4%; P=0.025). The most predominant component among the study population was central obesity (raised WC) (72.8%). Hypertriglyceridemia was found to be the strongest predictor of MetS among our participants (OR: 118.13; 95% CI: 33.79-412.77; P < 0.001).Conclusion:Our study discloses a very high prevalence of MetS among the participants, and a significant female predominance, with central obesity the commonest Mets component. The results suggest that hypertriglyceridemia is the strongest predictor of metabolic syndrome in our study participants.

Insulin-like growth factor (IGF) system and hormonal-metabolic profile in women with polycystic ovary syndrome.

No significant differences in serum IGFBP-3 (p=0.534), IGF-1 (p=0.29) and IGF-2 (p=0.56) between two groups have been detected. IGFBP-3 was in positive correlation with total cholesterol (p=0.026), LDL cholesterol (p=0.03) and triacylglycerols (p=0.022). IGF-1 were negatively correlated with insulin (p=0.022), HOMA IR (p=0.033), triacylglycerols (p=0.0196) and waist circumference (p=0.049). A positive correlation was detected between IGF-1 and HDL cholesterol (p=0.025). No significant relationship was observed between IGF-1 and steroid hormones. Serum levels of IGF-1, IGF-2 and IGFBP-3 in obese PCOS women do not differ from those detected in non‑obese PCOS women. IGF-1 negatively correlated with metabolic parameters, indicating that lower IGF-1 may represent an important predictor of metabolic syndrome (MS) in PCOS women. All peptides seem to have little effect on ovarian steroidogenesis in PCOS (Tab. 1, Fig. 1, Ref. 30).

Metabolic Control and Determinants Among HIV-Infected Type 2 Diabetes Mellitus Patients Attending a Tertiary Clinic in Botswana.

PurposeWe primarily aimed at determining the prevalence of metabolic syndrome and abnormal individual metabolic control variables in HIV-infected participants as compared to HIV-uninfected participants given current concerns. Our secondary objective was to determine the predictors of metabolic syndrome and individual metabolic control variables among the study participants to guide future management.Patients and MethodsA descriptive, case-matched cross-sectional study for four months from 15th June 2019 to 15th October 2019 at Block 6 Diabetes Reference Clinic in Gaborone, Botswana. We compared the proportions of metabolic syndrome and individual metabolic control variables based on gender and HIV status by means of bivariate analysis (Chi-squared test or Fisher’s exact test) to determine factors associated with metabolic control. A p-value of less than 0.05 was considered statistically significant.ResultsOverall, 86% of the study participants were found to have metabolic syndrome by International Diabetes Federation (IDF) criteria with 79.8% among HIV-infected and 89.1% among HIV-negative participants (p-value = 0.018). Older age was significantly associated with metabolic syndrome (p-value = 0.008). Female gender was significantly associated with metabolic syndrome as compared to male gender (P-value < 0.001), and with a statistically significant higher proportion of low HDL-C compared to males (P-value < 0.001). Female participants were significantly more likely to be obese as compared to males (P-value < 0.001). High triglycerides were more common in HIV-infected compared to HIV-negative participants (P-value = 0.004). HIV-negative participants were more likely to be obese as compared to HIV-infected participants (P-value = 0.003).ConclusionMetabolic syndrome is an appreciable problem in this tertiary clinic in Botswana for both HIV-infected and HIV-negative participants. Future prospective studies are warranted in our setting and similar sub-Saharan settings to enhance understanding of the role played by HAART in causing the metabolic syndrome, and the implications for future patient management.

Evaluation of anthropometric indices as metabolic syndrome predictors in Ecuadorian Military Personnel

Anthropometric measurements are simple and effective techniques for central or abdominal obesity evaluation. Although it is known their good predicting value, there is not a consensus about which is best in Metabolic Syndrome (MetSyn) diagnostic, using ATP III criteria. Anthropometric measurements included waist circumference (WC), waist hip ratio (WHR), waist height ratio (WHtR) and body mass index (BMI). This study aimed to determine the prevalence of MetSyn and compare anthropometric indices for optimal predicting value with their respective cut-offs for MetSyn diagnosis among army members in ESFORSE, Ecuador. The study includes 181 participants (175 male and 6 female), with mean age 37 ± 6 years, MetSyn prevalence is 8%, with WC (p &lt;.001), WHtR (p. .009) and WHR (p .020) as variables statistically significant. We analyzed the area under the curve (AUC) in a receiver operating characteristic (ROC) curve, in anthropometric measurements. Thus, WC and WHtR represent the highest AUC (WC: 0.77, 95% CI 0.69-0.86; WHtR: 0.70, 95% CI 0.59-0.82). The optimal cut-off values for predicting MetSyn are 92 cm in WC, 0.52 in WHtR and 0.93 in WHR. Therefore, the army members have a low prevalence of MetSyn, with WC as the best predicting value.

Evaluation of anthropometric indices as metabolic syndrome predictors in Ecuadorian Military Personnel

Anthropometric measurements are simple and effective techniques for central or abdominal obesity evaluation. Although it is known their good predicting value, there is not a consensus about which is best in Metabolic Syndrome (MetSyn) diagnostic, using ATP III criteria. Anthropometric measurements included waist circumference (WC), waist hip ratio (WHR), waist height ratio (WHtR) and body mass index (BMI). This study aimed to determine the prevalence of MetSyn and compare anthropometric indices for optimal predicting value with their respective cut-offs for MetSyn diagnosis among army members in ESFORSE, Ecuador. The study includes 181 participants (175 male and 6 female), with mean age 37 ± 6 years, MetSyn prevalence is 8%, with WC (p &lt;.001), WHtR (p. .009) and WHR (p .020) as variables statistically significant. We analyzed the area under the curve (AUC) in a receiver operating characteristic (ROC) curve, in anthropometric measurements. Thus, WC and WHtR represent the highest AUC (WC: 0.77, 95% CI 0.69-0.86; WHtR: 0.70, 95% CI 0.59-0.82). The optimal cut-off values for predicting MetSyn are 92 cm in WC, 0.52 in WHtR and 0.93 in WHR. Therefore, the army members have a low prevalence of MetSyn, with WC as the best predicting value.