Predictors Of Metabolic Syndrome Research Articles

The association between body image perception and metabolic syndrome in normal-weight adults.

This study analyzed the association between metabolic syndrome and its components according to body image perception in normal-weight adults. Management of chronic diseases that are the main cause of death in Korea is essential. The representative cause of the increase in these chronic diseases is metabolic syndrome, and preventing it is essential for chronic disease management. For data analysis, this study used data from Korea National Health and Nutritional Examination Survey (KNHANES-VII), 2016-2019. A total of 6479 survey respondents with normal BMI, aged 19 to 64 years old, were finally selected for analysis. Analysis was performed separately for men and women because gender-dependent differences were observed in the self-perceived body image types (underestimation, congruence, and overestimation groups). The incidence and risk of metabolic syndrome-related indicators according to body image perception were analyzed. As a result, it was found that men tending toward underestimation had lower prevalence and risk of metabolic syndrome and women tending toward overestimation had higher prevalence and risk of metabolic syndrome. This suggests that even individuals with the same BMI can have effects on the prevalence and risk of metabolic syndrome depending on their body image perception. This allows the conclusion that subjective body image perception can function as a supplementary predictor of metabolic syndrome.

Serum Neprilysin Is a Significant Predictor of Metabolic Syndrome in Psoriasis Patients

Serum Neprilysin Is a Significant Predictor of Metabolic Syndrome in Psoriasis Patients

Selenium as a predictor of metabolic syndrome in middle age women.

Selenium plays an important role in metabolic homeostasis. It has been suggested that it may also affect the expression and activity of PPAR-γ. The aim of study was to analyze the relationships between these variables in the context of the health of women, for whom the risk of MetS increases with age. The study involved 390 women in middle age. The stages of study: a survey-based part; anthropometric measurements; analysis of biological material (blood) in terms of glycemia, triglyceride, HDL, and selenium levels, as well as genetic analysis of the PPAR-γ polymorphisms. It was found that selenium may moderate the effect of the G allele of the PPAR-γ gene on the occurrence of elevated waist circumference (OR=1.030, 95%CI 1.005-1.057, p=0.020); and the effect of the C (OR=1.077, 95%CI 1.009-1.149, p=0.026) and the G alleles (OR=1.052, 95%CI 1.025-1.080, p<0.000) on the odds of elevated blood pressure. Women in whom HDL levels were not significantly reduced, had higher selenium levels (p=0.007). 1. The effect of selenium on MetS and its components has not been demonstrated. 2. The effect of individual alleles of the PPAR-γ gene on MetS and its components was not demonstrated. 3. The concentration of selenium may affect waist circumference in carriers of the G allele, and arterial hypertension in carriers of the C and G alleles by affecting the expression of PPAR-γ. 4. Higher selenium concentrations increased the odds of higher HDL levels in the group of subjects meeting the MetS criteria.

A Novel Clinical Predictor of Metabolic Syndrome: Vascular Risk Age

A Novel Clinical Predictor of Metabolic Syndrome: Vascular Risk Age

Prediction of Metabolic Syndrome in U.S. Adults Using Homeostasis Model Assessment-Insulin Resistance.

Background: The prevalence of obesity among U.S. adults has risen steadily over recent decades. Consequently, interest in identification of those at greatest metabolic risk necessitates the periodic assessment of underlying population characteristics. Thus, the aim of this study is to assess the efficacy of using insulin resistance (IR) as a predictor of metabolic syndrome (MetS). Methods: We performed a serial, cross-sectional analysis of nationally representative data from the National Health and Nutrition Examination Survey (NHANES). Data included nonpregnant adults who participated in NHANES between 2011 and 2018. IR was estimated using the homeostasis model assessment (HOMA). Optimal HOMA-IR cut points for MetS were identified using receiver operating characteristic curve analysis. Results: Data from 8897 participants representing 222 million individuals were analyzed. The estimated prevalence of MetS was 31.7% (n = 2958; 95% confidence interval 30.1-33.3). The optimal HOMA-IR to discriminate between individuals with and without MetS in the general population was 2.83 (sensitivity = 73.8%; specificity = 73.8%; area under the curve = 0.82). Conclusion: The HOMA-IR is a sensitive and specific method of screening for individuals with MetS. Prospective evaluation of this approach's efficacy in identifying those at risk for progression to MetS is warranted.

Incidence and predictors of metabolic syndrome in Asian-Indians: a 10-year population-based prospective cohort study.

Metabolic syndrome represents aggregation of risk factors associated with an increased risk of developing type 2 diabetes mellitus (DM) and atherosclerotic cardiovascular disease (ASCVD). Assessing its incidence is an effective way for estimating the future burden of DM and ASCVD and understanding their secular trends and effect of public health measures on halting the evolution of risk factors. The present study aimed to estimate the incidence of metabolic syndrome and its predictors using a population-based cohort. A subset of Chandigarh Urban Diabetes Study cohort (n = 1023) without diabetes or metabolic syndrome was prospectively evaluated after a mean of 10.7years. Metabolic syndrome was defined as per International Diabetes Federation criteria and diabetes as per American Diabetes Association standards. The incidence was calculated in 1000 person years, and multivariate logistic regression was used to estimate the strength of association between incident metabolic syndrome and risk factors. In the followed-up individuals (n = 303), incidence of metabolic syndrome was 32.1 per 1000 person years (95% CI 26.3-38.7 per 1000 person years). Amongst those developing metabolic syndrome, ≥4 components were present in 52% individuals, with low HDL-C being the most common abnormality. Those with metabolic syndrome had a five-time higher risk of diabetes (OR: 4.94; 95% CI: 2.27-9.96; p < 0.001) and a threefold higher risk of hypertension (OR: 2.67; 95% CI: 1.30-5.48; p = 0.006). Asian-Indians have a high incidence rate of metabolic syndrome, which is associated with sedentary lifestyle and consequent central obesity.

Eating Habit as Lifestyle Predictors of Metabolic Syndrome in Coal Mining Workers

Introduction: Previous study was carried out in a company, obtaining the prevalence of metabolic syndrome cases by 21.58% with non-communicable diseases as the indicator. The cause of the metabolic syndrome is critical to understand in order to reduce the impact of acute non-communicable diseases. Excessive food consumption and low physical activity in office workers and coal mining workers are two risk factors that contribute to the development of metabolic syndrome. Therefore, current research was conducted aiming to identify the lifestyle aspects related to metabolic syndrome in coal mining companies in South Kalimantan. Methods: This study was carried out through analytical observational cross-sectional research. In this case, the data were collected using questionnaires. Exercise routines, cigarette smoking, and meal frequency were the research factors. In South Kalimantan, there are up to 70 employees of mining company, and 22 people of them were selected as the research subjects through purposive random sampling and inclusion criteria. Results: The indicators of metabolic syndrome in most of the respondents showed normal state. However, a small number of respondents were at risk of having the indicators of metabolic syndrome. Meanwhile, based on the statistical analysis, there is a lifestyle factor that correlates with the frequency of eating coconut milk-based chicken curry (1-2 times/week) with metabolic syndrome (p=0.045). Conclusion: Types of food cooked using coconut milk can trigger a person to have a risk of experiencing one or several of the metabolic syndrome indicators. Things that can be done to reduce the risk of metabolic syndrome associated with the frequency of habit of eating high-fat animal side dishes, including reducing the frequency of such food at night.

Adiposity Indices as Predictors for Metabolic Syndrome Among Bangladeshi Women: A Cross Sectional Study

Adiposity Indices as Predictors for Metabolic Syndrome Among Bangladeshi Women: A Cross Sectional Study

Prevalence and Predictors of Metabolic Syndrome and Its Association with Vitamin D Deficiency in Patients with Newly Onset Type 2 Diabetes Mellitus: A Cross Sectional Study

Prevalence and Predictors of Metabolic Syndrome and Its Association with Vitamin D Deficiency in Patients with Newly Onset Type 2 Diabetes Mellitus: A Cross Sectional Study

Adrenal incidentaloma: Do patients with apparently nonfunctioning mass or autonomous cortisol secretion have similar or different clinical and metabolic features?

Although there is growing evidence associating nonfunctioning adrenal incidentalomas (NFAI) with cardiovascular risk factors, there are limited data whether NFAI and autonomous cortisol secretion (ACS) groups have similar or different clinical and metabolic features. The aim of this study is to compare cardiometabolic clinic parameters among patients with ACS and NFAI, as well as controls. Cross-sectional study. Eighty nine NFAI, 58 ACS and 64 controls were evaluated. Diagnosis of NFAI (1 mg dexamethasone suppression test [1 mg-DST] ≤50 nmol/L [≤1.8 μg/dl]) and ACS (1 mg-DST > 50 nmol/L [> 1.8 μg/dl]) was established according to current guidelines. The control group was selected based on a normal adrenal imaging exam. There were no differences between groups regarding age, gender, ethnicity, menopause or body mass index. Patients with adrenal incidentaloma presented higher frequency of hypertension (74.1 vs. 57.8%; p = .02), resistant hypertension (45.4 vs. 9.4%; p < .001), dyslipidemia (80.1 vs. 63.9%; p = .01), as well as metabolic syndrome (84.2 vs. 61.7%; p = .001) compared to the controls, respectively. NFAI and ACS patients presented similar frequency of arterial hypertension (70.8 vs. 79.3%) and resistant hypertension (41.3 vs. 51.1%), dyslipidemia (79.3 vs. 81.5%) and metabolic syndrome (83.3 vs. 85.7%); also, levels of HbA1c were similar between the groups. Binary logistic regression showed that NFAI (p = .004) and ACS (p = .001) were independent predictors for resistant hypertension (p = .003); also, ACS was an independent predictor for metabolic syndrome (p = .04). NFAI and ACS presented a higher frequency of cardiometabolic morbidities in comparison with individuals with normal adrenal glands. Additionally, we demonstrated that both ACS and NFAI groups have similar cardiometabolic conditions.

Assessment of metabolic syndrome predictors in relation to inflammation and visceral fat tissue in older adults

The diagnosis of metabolic syndrome (MetS) focuses on the assessment of risk factors such as insulin resistance, dyslipidemia, central adiposity and elevated blood pressure. Evidence suggests that markers of systemic inflammation may also be included in the definition of MetS and play some role in its pathogenesis. The study was designed to evaluate low-grade inflammation status in older adults with MetS in relation to increased body fat tissue and an attempt was made to evaluate new predictors for MetS through the analysis of the ROC Curve. Ninety-six middle-aged (69.2 ± 4.9) individuals from University of Third Age (women n = 75 and men n = 21) were allocated to two groups: without metabolic syndrome (n = 37) and with metabolic syndrome (n = 59) according to International Diabetes Federation criteria in agreement with American Heart Association/National Heart, Lung and Blood Institute 2009. Participants’ current health status was assessed using medical records from a routine follow-up visit to a primary care physician. Statistical analysis was performed using R studio software. Depending on the normal distribution, ANOVA or the Kruskal–Wallis test was used. The optimal threshold value for clinical stratification (cut-off value) was obtained by calculating the Youden index. The AUC was observed to be the highest for a new anthropometric index i.e. lipid accumulation product (0.820). Low-grade inflammation dominated in MetS group (BMI 28.0 ± 4.4 kg/m2, WHR 0.9 ± 0.1, FM 24.7 ± 7.9 kg) where significantly higher values of TNF-α (p = 0.027) and HGMB-1 protein (p = 0.011) were recorded.The optimal threshold values for immunological indices assessed as new predictors of the metabolic syndrome were: 93.4 for TNF-α, 88.2 for HGMB-1 protein and 1992.75 for ghrelin. High AUC values for these indices additionally confirmed their high diagnostic usefulness in MetS.

Clinical and biochemical profile of babies born to mothers with gestational diabetes mellitus

Background: Diabetes is one of the most common endocrine disorder affecting women during pregnancy. The incidence of pregestational and gestational diabetes is increasing in India. Gestational diabetes mellitus (GDM) can be a predictor of future overt diabetes in mother and a predictor for metabolic syndrome in the baby in future. Diabetic control is key factor in determining fetal and maternal outcome during pregnancy. As gestational diabetes has got a very significant impact on the mother and the baby, we aim at studying the clinical and biochemical profile of babies born to mothers with GDM. The data indicates that perinatal morbidity and mortality in the offspring of women with diabetes mellitus have improved with dietary management and insulin therapy. However, complication may still arise in the infant including hypoglycemia, hypocalcemia, hypomagnesemia, perinatal asphyxia, respiratory distress syndrome, cardiac abnormalities, polycythemia, hyperbilirubinemia, macrosomia, birth injuries, and congenital malformation. Aims and Objectives: The aim of the study was to study the clinical and biochemical profile of babies born to mothers with GDM. Materials and Methods: This study is a hospital-based, retrospective, and observational study which includes all the babies born to mothers with GDM, in Sree Utradam Thirunal Academy of Medical Sciences during the 12-month period from November 1, 2014, to October 31, 2015. Results: Most of our mothers with GDM were of the age group 20–30 years, were from below poverty line families, and were mostly from urban areas. Most of our mothers were primigravida. The majority had controlled blood sugar. GDM was most frequently detected in the second trimester (64.9%). In terms of treatment, a significant number of GDM patients are with diet (44.6%), while 39.2% required insulin. The most common mode of delivery included vaginal (58.1%) followed by lower segment caesarean section (LSCS). The most common indications for LSCS were a previous cesarean section (12.2%) and failed induction (9.5%). Most of the babies born to diabetic mothers in our study cried immediately after birth and did not need any resuscitation. A significant proportion of babies born to diabetic mothers experienced hypoglycemia, with 4.1% showing symptomatic signs. A substantial number had birth weights within the normal range. The majority had favorable 1 min and 5 min APGAR scores, and most did not have congenital anomalies. About 55.4% were exclusively breastfed, while 43.2% received a combination of breast milk and formula. Majority had serum bilirubin levels below 11 mg/dL (55.4%). In terms of thyroid function (TSH), the majority of babies had TSH levels below 16 (89.2%). Most babies had hemoglobin levels below 22 g/dL (97.3%), and their serum calcium levels (Calcium) were mostly &gt;9 mg/dL (56.8%). Conclusion: Pre-pregnancy counseling and screening for pre-GDM help women to maintain optimal blood sugar levels. This helps in better antenatal, intrapartum, and postnatal outcome. Babies of diabetic mothers with optimal blood sugar control have better obstetric and neonatal outcome. Complications are less among these patients.

Computed tomographic abdominal fat volume estimation - a handy tool to predict the risk of metabolic syndrome.

Abdominal obesity plays a significant role in the development of metabolic syndrome, with individual metabolic risk profiles for visceral and subcutaneous adipose tissues. This study aimed to calculate and correlate the subcutaneous, visceral, and total fat compartment volume in metabolic and non-metabolic syndrome patients. This was a cross-sectional study conducted on 112 patients categorized into Group A (with metabolic syndrome) and Group B (without metabolic syndrome). They were subjected to computed tomography (CT) study of the abdomen using a 128-slice MDCT scanner. Body mass index (BMI), visceral fat volume (VFV), subcutaneous fat volume (SFV), and total fat volume (TFV) were calculated and correlated with biochemical evidence of metabolic syndrome. The mean age of patients in Group A was 60.91 ± 12.23 years as compared to Group B, which was 50.12 ± 16.30 years. Overall, a male predominance was observed, i.e. 69 cases (61.6%). BMI was proven to be an inaccurate risk predictor. However, mean VFV, SFV, and TFV was statistically higher in patients with metabolic syndrome (p = 0.001), with visceral fat volume predicting a higher risk in females (p = 0.026). Abdominal CT is a commonly performed yet unexplored tool for the risk assessment of metabolic syndrome. Through the results obtained in this study, we have proven the need for calculating SFV, VFV, and TFV as predictors of metabolic syndrome in comparison to the conventional practice of BMI assessment. The radiologist can thus work with the clinician to effectively detect and treat this health condition.

CRP/HDL-C and Monocyte/HDL-C ratios as Predictors of Metabolic Syndrome in Patients With Type 2 Diabetes Mellitus.

Metabolic syndrome (MetS) denotes a cluster of co-occurring medical conditions associated with regulating hyperglycemia and acute cardiovascular events and complications. The escalating frequency of MetS among individuals afflicted with type 2 diabetes mellitus (T2DM) underscores its burgeoning significance as a critical public health concern and a complex clinical conundrum. Timely identification is imperative to avert the expedited progression of diabetic complications. To investigate the role of CRP/HDL-C and Monocyte/HDL ratios in predicting MetS in T2DM individuals. The study was designed as a two-year prospective study and included 80 T2DM patients divided into MetS and non-MetS groups based on MetS development over two years. The patients' serums were analyzed for complete blood count parameters, lipid profile, and C-reactive protein (CRP). Based on the laboratory test results, Monocyte/HDL-C and CRP/HDL-C ratios were calculated and analyzed. The receiver operating characteristic (ROC) curve and their corresponding areas under the curve (AUC) were used to determine prognostic accuracy. Monocyte/HDL-C ratio and CRP/HDL-C ratio were significantly higher in MetS-T2DM2 than in nonMetS-T2DM (p=0.003 and p=0.029, respectively). The results of ROC curve analysis have shown that the CRP/HDL-C ratio (AUC of 0.695) and Monocytes/HDL-C ratio (AUC of 0.645) can serve as good predictors of MetS in T2DM patients. This study confirms the reliability of the Monocytes/HDL-C and CRP/HDL-C ratios as novel, simple, low-cost, and valuable predictors of MetS development in T2DM.

Obesity: An important predictor of metabolic syndrome

Background/Aim: The leading avoidable cause of mortality in the world is obesity. It modifies how the body reacts to insulin, which might result in insulin resistance and an elevated risk of type 2 diabetes. Recent investigations have revealed a link between obesity and the metabolic syndrome. Therefore, it was intended for the current study to look at the prevalence of obesity and how it relates to the metabolic syndrome. Methods: 120 healthy males between 30-50 years of age were chosen from the general population of Kota District, Rajasthan, India and screened for obesity and divided in three groups: normal, overweight and obese. Each group comprised of forty subject. Serum was separated and run in department of biochemistry , GMC Kota. Anthropometric parameters were taken. The completely automated analyser ERBA EM 360 performed lipid profile and blood sugar analyses on serum. Result: Obesity increased metabolic syndrome prevalence. In comparison to overweight and normal weight people, obese subjects exhibited considerably lower levels of high-density lipoprotein (HDL) cholesterol and significantly higher levels of blood glucose, triglycerides, total cholesterol and low-density lipoprotein (LDL) cholesterol. Additional coronary artery disease (CAD) risk prediction ratios, such as total cholesterol/HDL, LDL/HDL and triglycerides/ HDL ratios that have gradually increased from the normal to obese group, show that obese subjects have a relatively higher risk of developing cardiovascular diseases (CVD) than do those in the overweight and normal groups. Conclusion: One of the key elements of metabolic syndrome, which is a collection of clinical and metabolic anomalies including abdominal obesity, insulin resistance, hypertension and dyslipidaemia, is obesity. Each of these conditions raises the risk of CVD and diabetes mellitus type 2 directly. The progression towards diabetes and CVD can be prevented by lifestyle modification programmes and regular health checks (to explore the risk factors of metabolic syndrome).

Omentin as an Independent Predictor of Metabolic Syndrome and Obesity Among Adolescents in Northeast China.

We investigated the association of omentin with metabolic syndrome (MetS), MetS components, and obesity in adolescents. A total of 742 middle-school students from Liaoyang City were enrolled in this cross-sectional study using the stratified cluster sampling method. Clinical information and blood samples were collected, and serum omentin levels were measured using enzyme-linked immunosorbent assay. Mean plasma omentin levels were lower in male than in female participants (88.25 (interquartile range 63.02-133.61) vs 99.46 (interquartile range 69.08-188.35) ng/L, P = 0.004). The participants were divided into four groups according to the quartile (Q) values of omentin from low to high. With increasing omentin levels from Q1 to Q4, the age of adolescents and the proportion of males gradually increased (P < 0.05), whereas the body mass index (BMI) (P < 0.05) and prevalence of MetS (P > 0.05) tended to decrease. Omentin levels were significantly and negatively correlated with waist circumference and BMI (correlation coefficients of -0.099 and -0.115, respectively). Regression analysis showed that omentin level was independently associated with the risk of MetS (Odds ratio, OR = 0.639, 95% confidence interval, CI (0.432, 0.945)), which was attributed to the association with central obesity (OR = 0.775, 95% CI (0.605, 0.993)) among MetS components. Increased omentin levels also indicated a reduced risk of obesity (OR = 0.700, 95% CI (0.563, 0.870)). Omentin is an independent predictor of MetS and obesity among adolescents in northeast China.

Triglyceride-to-High-Density-Lipoprotein-Cholesterol Ratio as a Predictor of Metabolic Syndrome According to Stage of Life at Obesity Onset in Women with Severe Obesity—A Pilot Study

The triglyceride-to-high-density lipoprotein-cholesterol (TG/HDL-c) ratio is a simple but effective indicator of metabolic imbalance that characterizes metabolic syndrome (MetS) and can consequently indicate a higher cardiovascular risk. It may, therefore, be useful in identifying a high risk for cardiometabolic diseases according to the onset of obesity. The aim of this study was to evaluate the association between MetS and the stage of life at obesity onset and to establish the cutoff point for the TG/HDL-c ratio as a marker of MetS in women with severe obesity. Forty-seven women who were to undergo bariatric surgery were evaluated. Anthropometric and metabolic parameters were measured, and the TG/HDL-c ratio was calculated. The volunteers were grouped according to their stage of life at obesity onset. A receiver operating characteristic (ROC) curve was constructed to define cutoff points for the TG/HDL-c ratio as predictors of MetS. Women who developed obesity early (during infancy/adolescence) had higher weight (p = 0.008), body mass index (p = 0.031), and hip circumference (p = 0.036) than those who developed obesity later (in adulthood); however, no association was found between obesity onset and MetS. The cutoff points for the TG/HDL-c ratio that were established for those who developed early or late obesity were 2.30 and 2.19, respectively. Although the stage of life at the onset of obesity was not related to MetS, different cutoff points for the TG/HDL-c ratio were observed.

Abstract 15367: Depression Symptom Patterns as Predictors of Metabolic Syndrome and Cardiac Events in Symptomatic Women With Suspected Myocardial Ischemia: The Women’s Ischemia Syndrome Evaluation (WISE &amp; WISE-CVD) Projects

Introduction: Ischemic Heart Disease (IHD) risk in women includes biomedical, behavioral, and psychosocial contributors. Among psychosocial contributors, recent studies suggest that depression, especially somatic symptoms of depression such as anhedonia and low energy, may play a disproportionate role in the development of both IHD risk factors and major adverse cardiovascular events (MACE). Methods: We examined relationships between cognitive/somatic symptoms of depression and metabolic syndrome (MetS) in two independent cohorts of women with suspected IHD. In the Women’s Ischemia Syndrome Evaluation (WISE, NCT00000554), we also examined depression and MetS as predictors of all-cause mortality and MACE over a median 9.3-year follow-up. The sample from WISE included 641 women with suspected ischemia with or without obstructive coronary artery disease (CAD). The WISE-Coronary Vascular Dysfunction (WISE-CVD, NCT00832702) consisted of 359 women with suspected ischemia and no obstructive CAD (INOCA). Somatic, cognitive, and total depressive symptoms were measured via the Beck Depression Inventory (BDI). MetS was assessed according to the AHA’s ATP-III criteria. Results: (See attached table) In both the WISE and WISE-CVD samples, somatic symptoms of depression were associated with MetS diagnosis and MetS severity, while cognitive symptoms were not. Within the WISE sample, using Cox Proportional Hazard Regression, both somatic symptoms and MetS diagnosis were significant predictors of all-cause mortality and MACE, while cognitive symptoms were not. Conclusions: In two independent samples of women undergoing coronary angiography for suspected myocardial ischemia, somatic symptoms of depression were uniquely associated with both MetS and all-cause mortality and MACE, and both somatic symptoms of depression and MetS independently predicted all-cause mortality and MACE.

Depression Symptom Patterns as Predictors of Metabolic Syndrome and Cardiac Events in Symptomatic Women with Suspected Myocardial Ischemia: The Women's Ischemia Syndrome Evaluation (WISE and WISE-CVD) Projects

Background: Ischemic heart disease (IHD) risk in women includes biomedical, behavioral, and psychosocial contributors. The purpose of this study was to build upon previous research suggesting that in women, somatic symptoms (SS) of depression may be important to the development of IHD risk factors and major adverse cardiovascular events (MACE). Based on previous findings, we hypothesized that: (1) SS would be associated with robust biomedical predictors of heart disease and functional capacity, while cognitive symptoms (CS) of depression would not, and (2) SS would independently predict adverse health outcomes while CS would not. Methods: We examined the relationships between symptoms of depression (SS/CS), metabolic syndrome (MetS), inflammatory markers (IM), coronary artery disease (CAD) severity, and functional capacity in two independent cohorts of women with suspected IHD. In the Women's Ischemia Syndrome Evaluation (WISE), we also examined these variables as predictors of all-cause mortality (ACM) + MACE over a median 9.3-year follow-up. The WISE sample included 641 women with suspected ischemia with or without obstructive CAD. The WISE-Coronary Vascular Dysfunction (WISE-CVD) sample consisted of 359 women with suspected ischemia and no obstructive CAD. All study measures were collected uniformly at baseline. Depressive symptoms were measured via the Beck Depression Inventory. MetS was assessed according to Adult Treatment Panel III (ATP-III) criteria. Results: In both studies, SS was associated with MetS (Cohen's d = 0.18, 0.26, P &lt; 0.05, respectively), while CS was not. Within WISE, using Cox Proportional Hazard Regression, SS (Hazard ratio [HR] = 1.08, 95% confidence interval [CI] = 1.01–1.15; HR = 1.07, 95% CI = 1.00–1.13) and MetS (HR = 1.89, 95% CI = 1.16–3.08; HR = 1.74, 95% CI=1.07–2.84) were independent predictors of ACM + MACE after controlling for demographics, IM, and CAD severity, while CS was not. Conclusions: In two independent samples of women undergoing coronary angiography due to suspected ischemia, SS but not CS of depression were associated with MetS, and both SS and MetS independently predicted ACM and MACE. These results add to previous studies suggesting that SS of depression may warrant specific attention in women with elevated cardiovascular disease (CVD) risk. Future research evaluating the biobehavioral basis of the relationship between depression, MetS, and CVD is needed.

Fat to lean mass ratio in spinal cord injury: Possible interplay of components of body composition that may instigate systemic inflammation and metabolic syndrome

Objective To investigate the relationships between percentage fat mass (%FM), percentage lean mass (%LM), and the ratio of %FM to %LM with pro-inflammatory adipokines and metabolic syndrome in individuals with chronic spinal cord injury (SCI). Design Observational, cross-sectional. Linear and logistic regression were used to examine the associations between the %FM, %LM, and the %FM to %LM ratio with inflammatory markers and metabolic syndrome, respectively. Participants Seventy chronic SCI men and women. Main Outcome Measures %FM, %LM, %FM to %LM ratio; fasting lipids, glucose, and tumor necrosis factor alpha (TNF-α), interleukin-6 (IL-6), and high-sensitivity c-reactive protein (hs-CRP); metabolic syndrome as determined by The International Diabetes Federation criteria. Results There were significant correlations between %FM, %LM and the %FM to %LM ratio with hs-CRP. The %LM beta coefficient value was negative and greater than the beta coefficient value for %FM. The %FM to %LM ratio had the strongest correlation with hs-CRP and showed the only significant relationship with IL-6. There were strong significant correlations between %FM, %LM and the %FM to %LM ratio with metabolic syndrome. However, the %FM to %LM ratio, again, showed the strongest relationship indicating that it may be the best predictor of metabolic syndrome. Conclusion Both higher %FM and lower %LM affect cardiometabolic health and can be used as predictors for metabolic syndrome. However, the %FM to %LM ratio was the best predictor of systemic inflammation and cardiometabolic disorders in this group of SCI participants, suggesting that they both contribute to the statistical model.