Predictive performances of lipid accumulation product vs. adiposity measures for cardiovascular diseases and all-cause mortality, 8.6-year follow-up: Tehran lipid and glucose study

<p>Abstract</p> <p>Background</p> <p>The body mass index (BMI) is the most commonly used marker for evaluating obesity related risks, however, central obesity measures have been proposed to be more informative. Lipid accumulation product (LAP) is an alternative continuous index of lipid accumulation. We sought in this study to assess if LAP can outperform BMI, waist-to-height-ratio (WHtR), or waist-to-hip-ratio (WHpR) in predicting incident cardiovascular disease (CVD) or all-cause mortality.</p> <p>Results</p> <p>Among participants of Tehran Lipid and Glucose Study, 6,751 participants (2,964 men), aged ≥ 30 years, were followed for a median of 8.6 years. We observed 274 deaths (men: 168) and 447 CVD events (men: 257). Levels of common CVD risk factors significantly increased across LAP quartiles. Mortality rates did not differ by LAP quartiles. Among participants free of CVD at baseline [6331 (2,741 men)], CVD incident rates per 1000 person increased in a stepwise fashion with increasing LAP quartile values in both men (from 6.9 to 17.0) and women (from 1.3 to 13.0), (Ps < 0.001).</p> <p>Among women, a 1-SD increment in log-LAP conferred a 41% increased risk for CVD (HR 1.41, 95% CIs 1.02-1.96). Among men, however, LAP was not observed to be independently associated with increased risk of CVD; except in a sub-group of men assigned to the lifestyle modification interventions, where, LAP predicted CVD risk.</p> <p>After adjustment with CVD risk factors LAP turned to be inversely associated with risk of all-cause mortality (HR, men 0.74, 95% CIs 0.61-0.90; women, 0.94 95% CIs 0.74-1.20).</p> <p>Among women, magnitude of increased risk of CVD due to LAP was not different from those of anthropometric measures. Among men, however, WHpR was observed to be more strongly associated with increased risk of CVD than was LAP.</p> <p>Among neither men nor women were the predictive performances (discrimination, calibration, goodness-of-fit) of the LAP better than those of different anthropometric measures were.</p> <p>Conclusions</p> <p>If LAP is to be used for predicting CVD, it might not be superior to WHtR or WHpR.</p

Predictive performance of the visceral adiposity index for a visceral adiposity-related risk: Type 2 Diabetes

<p>Abstract</p> <p>Background</p> <p>Visceral adiposity index (VAI) has recently been developed based on waist circumference, body mass index (BMI), triglycerides (TGs), and high-density lipoprotein cholesterol (HDL-C). We examined predictive performances for incident diabetes of the VAI per se and as compared to the metabolic syndrome (MetS) and waist-to-height-ratio (WHtR).</p> <p>Methods</p> <p>Participants free of diabetes at baseline with at least one follow-up examination (5,964) were included for the current study. Weibull regression models were developed for interval-censored survival data. Absolute and relative integrated discriminatory improvement index (IDI) and cut-point-based and cut-point-free net reclassification improvement index (NRI) were used as measures of predictive ability for incident diabetes added by VAI, as compared to the MetS and WHtR.</p> <p>Results</p> <p>The annual incidence rate of diabetes was 0.85 per 1000 person. Mean VAI was 3.06 (95%CIs 2.99-3.13). Diabetes risk factors levels increased in stepwise fashion across VAI quintiles. Risk gradient between the highest and lowest quintile of VAI was 4.5 (95%CIs 3.0-6.9). VAI significantly improved predictive ability of the MetS. The relative IDI and cut-point free NRI for predictive ability added to MetS by VAI were 30.3% (95%CIs 18.8-41.8%) and 30.7% (95%CIs 20.8-40.7%), respectively. WHtR, outperformed VAI with cut-point-free NRI of 24.6% (95%CIs 14.1-35.2%).</p> <p>Conclusions</p> <p>In conclusion, although VAI could be a prognostic tool for incident diabetes events, gathering information on its components (WC, BMI, TGs, and HDL-C) is unlikely to improve the prediction ability beyond what could be achieved by the simply assessable and commonly available information on WHtR.</p

Diabetes prediction, lipid accumulation product, and adiposity measures; 6-year follow-up: Tehran lipid and glucose study

<p>Abstract</p> <p>Background</p> <p>The body mass index (BMI) is the most commonly used marker for evaluating obesity related risks, however, central obesity measures have been proposed to be more informative. Lipid accumulation product (LAP) is an alternative continuous index of lipid accumulation, which is computed from waist circumference (WC, cm) and triglycerides (TGs, mmol/l): (WC-65) ×TG (men) and (WC-58) ×TG (women). We sought in this study to assess if LAP can outperform BMI, waist-to-height-ratio (WHtR), or waist-to-hip-ratio (WHpR) in identifying prevalent and predicting incident diabetes.</p> <p>Results</p> <p>The cross-sectional analyses were performed on a sample included 3,682 men and 4,989 women who were not pregnant, aged ≥ 20 years. According to the age (≥ 50 and <50 years) - and sex-specific analyses, odds ratios (ORs) of LAP for prevalent diabetes were higher than those of BMI, WHpR, or WHtR among women, after adjustment for mean arterial pressure and family history of diabetes. The OR of LAP in old men was lower than those of other adiposity measures; in young men, however, LAP was superior to BMI but identical to WHpR and WHtR in identifying prevalent diabetes. Except in young men, LAP showed highest area under the receiver operating characteristic curves (AROC) for prevalent diabetes (P for trend ≤ 0.005).</p> <p>For longitudinal analyses, a total of 5,018 non-diabetic subjects were followed for ~6 years. The ORs of BMI, WHpR, and WHtR were the same as those of LAP in both sexes and across age groups; except in young men where LAP was superior to the BMI. AROCs of LAP were relatively the same as anthropometric adiposity measures.</p> <p>Conclusions</p> <p>LAP was a strong predictor of diabetes and in young individuals had better predictability than did BMI; it was, however, similar to WHpR and WHtR in prediction of incident diabetes.</p

Comparison of artificial neural network, logistic regression and discriminant analysis methods in prediction of metabolic syndrome.

Introduction: Artificial neural networks as a modern modeling method have received considerable attention in recent years. The models are used in prediction and classification in situations where classic statistical models have restricted application when some, or all of their assumptions are met. This study is aimed to compare the ability of neural network models to discriminant analysis and logistic regression models in predicting the metabolic syndrome. Materials & Methods: A total of 347 participants from the cohort of the Tehran Lipid and Glucose Study (TLGS) were studied. The subjects were free of metabolic syndrome at baseling according to the ATPIII criteria. Demographic characteristics, history of coronary artery disease, body mass index, waist, LDL, HDL, total cholesterol, triglycerides, fasting and 2 hours blood sugar, smoking, systolic and diastolic blood pressure were measured at baseline. Incidence of metabolic syndrome after about 3 years of follow up was considered a dependent variable. Logistic regression, discriminant analysis and neural network models were fitted to the data. The ability of the models in predicting metabolic syndrome was compared using ROC analysis and the Kappa statistic, for which, MATLAB software was used. Results: The areas under receiver operating characteristic (ROC) curve for logistic regression, discriminant analysis and artificial neural network models (15: 8: 1) and (15: 10: 10) were estimated as 0. 749, 0. 739, 0. 748 and 0. 890 respectively. Sensitivity of models were calculated as 0. 483, 0. 677, 0. 453 and 0. 863 and their specificity as 0. 857, 0. 660, 0. 910 and 0. 844 respectively. The Kappa statistics for these models were 0. 322, 0. 363, 0. 372 and 0. 712 respectively. Conclusion: Results of this study indicate that artificial neural network models perform better than classic statistical models in predicting the metabolic syndrome

Prognostic significance of the Complex "Visceral Adiposity Index" vs. simple anthropometric measures: Tehran lipid and glucose study

<p>Abstract</p> <p>Background</p> <p>Visceral adiposity index (VAI) has recently been suggested to be used as a surrogate of visceral adiposity. We examined if VAI could improve predictive performances for CVD of the Framingham's general CVD algorithm (a multivariate model incorporating established CVD risk factors). We compared the predictive abilities of the VAI with those of simple anthropometric measures i.e. BMI, waist-to-height ratio (WHtR) or waist-to-hip ratio (WHpR).</p> <p>Design and methods</p> <p>In a nine-year population-based follow-up, 6 407 (2 778 men) participants, free of CVD at baseline, aged ≥ 30 years were eligible for the current analysis. The risk of CVD was estimated by incorporating VAI, BMI, WHpR, and WHtR, one at a time, into multivariate accelerated failure time models.</p> <p>Results</p> <p>We documented 534 CVD events with the annual incidence rate (95%CIs) being 7.3 (6.4-8.3) among women and 13.0 (11.7-14.6) among men. Risk of future CVD increased with increasing levels of VAI among both men and women. VAI was associated with multivariate-adjusted increased risk of incident CVD among women. However, the magnitude of risk conferred by VAI was not significantly higher than those conferred by BMI, WHpR, or WHtR. Among men, after adjustment for established CVD risk factors, VAI was no longer associated with increased risk of CVD. VAI failed to add to the predictive ability of the Framingham general CVD algorithm.</p> <p>Conclusions</p> <p>Using VAI instead of simple anthropometric measures may lead to loss of much information needed for predicting incident CVD.</p

New and known type 2 diabetes as coronary heart disease equivalent: results from 7.6 year follow up in a middle east population

<p>Abstract</p> <p>Background</p> <p>To investigate whether the known diabetes mellitus (KDM) or newly diagnosed diabetes mellitus (NDM) could be regarded as a coronary heart disease (CHD) risk equivalent among a relatively young Middle East population with high prevalence of diabetes mellitus (DM).</p> <p>Methods</p> <p>A population based cohort study of 2267 men and 2931 women, aged ≥ 30 years. Prior CHD was defined as self-reported or ECG positive CHD at baseline, KDM as subjects using any kind of glucose-lowering medications and NDM according to fasting plasma glucose and 2-h postchallenge glycemia.</p> <p>Participants were categorized to six groups according to the presence of known or newly diagnosed DM and CHD at baseline (DM-/CHD-, DM-/CHD+, NDM+/CHD-, NDM+/CHD+, KDM+/CHD-, KDM+/CHD+) and Cox regression analysis were used to estimate the hazard ratio (HR) of CHD events for these DM/CHD groups, given DM-/CHD-as the reference.</p> <p>Results</p> <p>During 7.6-year follow up, 358 CHD events occurred. After controlling traditional risk factors, HRs of CHD events for DM-/CHD+ group were 2.1 (95% CI: 1.4-3.1) and 5.2 (3.2-8.3) in men and women respectively. Corresponding HRs for NDM+/CHD-were 1.7 (1.1-2.7) and 3.1 (1.8-5.6) and for KDM+/CHD-were 1.7 (0.9-3.3) and 6.2 (3.6-10.6) in men and women respectively. The HRs for NDM+/CHD+ and KDM+/CHD+ groups (i.e. participants with history of both diabetes and CHD) were 6.4 (3.2-12.9) and 8.0 (4.3-14.8) in women and 3.2 (1.9-5.6) and 4.2 (2.2-7.8) in men, respectively.</p> <p>The hazard of CHD events did not differ between KDM+/CHD-and DM-/CHD+ in both genders using paired homogeneity test, however the HR for NDM+/CHD-was marginally lower than the HR for DM-/CHD+ in women (<it>p </it>= 0.085).</p> <p>Conclusions</p> <p>KDM patients in both genders and NDM especially in men exhibited a CHD risk comparable to nondiabetics with a prior CHD, furthermore diabetic subjects with prior CHD had the worst prognosis, by far more harmful in women than men; reinforcing the urgent need for intensive care and prophylactic treatment for cardiovascular diseases.</p

Data analysis and the relationship between doctors and patients with type-2 diabetes in the treatment process

Background &amp; Objective: Doctor-patient relationship plays an important role in adherence of patients to treatment instructions. This study tries to examine the relationship between physicians and patients with type 2 diabetes in the treatment process by the grounded theory. Materials and Methods: Eleven physicians and 9 diabetic patients in both sexes were selected from among all type 2 diabetic patients referred to physicians' offices in Shahid Beheshti University of Medical Sciences and Health Services. A semi-designed interview was used to gather information. Results: The factor influencing the physician's lived experiences in dealing with the patient and the patient's lived experiences in dealing with the physician was named as the "physician-patient discourse" factor. This factor included 9 categories in 2 central codes "physician-centered" and "patient-centered" in the physician's lived experiences with the patient and 4 categories in 2 central codes "awareness" and "confidence-building" in the patient's lived experiences in dealing with the physician. Conclusion: A discourse in which the physician allocates adequate time to efficiently convey training and information, and to take a complete history of the patient, and to establish an effective, friendly, and respectful relationship ultimately lead to the patient's trust. These factors can persuade the patient to adherence to the prescribed treatment

The Relationship between Metabolic Syndrome and Shift Work in Midwives: A Cross Sectional Study

AbstractIntroduction: Recent studies suggest that shift work can be associated with the incidence of metabolic syndrome. The present study was conducted in 2019 to investigate the relationship between metabolic syndrome and shift work in midwives working in hospitals affiliated to universities of medical sciences in Tehran, Iran.Methods: The present analytical cross-sectional study recruited 216 midwives who satisfied the inclusion criteria. Questionnaires were first used to collect demographic information and job records. Waist circumference and blood pressure of the subjects were then measured. A 12-hour fasting blood test was performed to determine fasting blood sugar (FBS), triglyceride and HDL levels. The frequency of metabolic syndrome was ultimately evaluated based on the Harmonized criteria. Data were analyzed in SPSS using the Chi-square and Fisher's exact tests.Results: The prevalence of metabolic syndrome was found to be 6.9% in the midwives using the Harmonized criteria. Although the prevalence of metabolic syndrome was higher in the night-shift workers (11.5%) compared to that in the other two groups, but the difference was not significant. Low HDL cholesterol and abdominal obesity were respectively the most frequent metabolic syndrome criteria. Significant relationships were observed between low HDL cholesterol and night shift (P&lt;0.001), and also between abdominal obesity and rotational shift work (P&lt;0.001).Conclusions: According to the present findings, a higher prevalence of metabolic syndrome was observed in the night-shift workers, and rotational shift work was found to be significantly associated with two of the metabolic syndrome criteria, namely low HDL levels and abdominal obesity

Artificial neural network design for modeling of mixed bivariate outcomes in medical research data

Background & Objective: Mixed outcomes arise when, in a multivariate model, response variables measured on different scales such as binary and continuous. Artificial neural networks (ANN) can be used for modeling in situations where classic models have restricted application when some of their assumptions are not met. In this paper, we propose a method based on ANNs for modeling mixed binary and continuous outcomes. Methods: Univariate and bivariate models were evaluated based on two different sets of simulated data. The

Lipid measures for prediction of incident cardiovascular disease in diabetic and non-diabetic adults: results of the 8.6 years follow-up of a population based cohort study

<p>Abstract</p> <p>Background</p> <p>Diabetes is a strong risk factor for cardiovascular disease (CVD).The relative role of various lipid measures in determining CVD risk in diabetic patients is still a subject of debate. We aimed to compare performance of different lipid measures as predictors of CVD using discrimination and fitting characteristics in individuals with and without diabetes mellitus from a Middle East Caucasian population.</p> <p>Methods</p> <p>The study population consisted of 1021 diabetic (men = 413, women = 608) and 5310 non-diabetic (men = 2317, women = 2993) subjects, aged ≥ 30 years, free of CVD at baseline. The adjusted hazard ratios (HRs) for CVD were calculated for a 1 standard deviation (SD) change in total cholesterol (TC), log-transformed triglyceride (TG), high density lipoprotein cholesterol (HDL-C), low density lipoprotein cholesterol (LDL-C), non-HDL-C, TC/HDL-C and log-transformed TG/HDL-C using Cox proportional regression analysis. Incident CVD was ascertained over a median of 8.6 years of follow-up.</p> <p>Results</p> <p>A total of 189 (men = 91, women = 98) and 263(men = 169, women = 94) CVD events occurred, in diabetic and non-diabetic population, respectively. The risk factor adjusted HRs to predict CVD, except for HDL-C, TG and TG/HDL-C, were significant for all lipid measures in diabetic males and were 1.39, 1.45, 1.36 and 1.16 for TC, LDL-C, non- HDL-C and TC/HDL-C respectively. In diabetic women, using multivariate analysis, only TC/HDL-C had significant risk [adjusted HR1.31(1.10-1.57)].Among non-diabetic men, all lipid measures, except for TG, were independent predictors for CVD however; a 1 SD increase in HDL-C significantly decreased the risk of CVD [adjusted HR 0.83(0.70-0.97)].In non-diabetic women, TC, LDL-C, non-HDL-C and TG were independent predictors.</p> <p>There was no difference in the discriminatory power of different lipid measures to predict incident CVD in the risk factor adjusted models, in either sex of diabetic and non-diabetic population.</p> <p>Conclusion</p> <p>Our data according to important test performance characteristics provided evidence based support for WHO recommendation that along with other CVD risk factors serum TC vs. LDL-C, non-HDL-C and TC/HDL-C is a reasonable lipid measure to predict incident CVD among diabetic men. Importantly, HDL-C did not have a protective effect for incident CVD among diabetic population; given that the HDL-C had a protective effect only among non- diabetic men.</p