Lipid accumulation product and visceral adiposity index for incidence of cardiovascular diseases and mortality; results from 13 years follow-up in Isfahan cohort study.

Background: /Aims: Visceral adiposity index (VAI) and lipid accumulation product (LAP) are novel anthropometric indices that have shown an association with metabolic syndrome; however, limited data are available regarding the predictive performance of these indices for the incidence of cardiovascular diseases (CVD) and mortality. Methods: This study was performed on the data retrieved from Isfahan Cohort Study (ICS). ICS is an ongoing population-based cohort study conducted in 3 counties in central Iran. Pearson correlation analysis was performed between LAP, VAI, and metabolic parameters. Cox regression analysis and receiver operative characteristics (ROC) curve analysis were performed in order to evaluate the ability of VAI and LAP for the incidence of CVD, CVD-associated mortality, and all-cause mortality. We further compared the predictive performance of VAI and LAP with body mass index (BMI). Results: LAP and VAI were significantly correlated with all metabolic variables, including blood pressure, fasting blood glucose, and lipid profile components. Univariate regression analysis indicated a significant association between LAP and VAI and CVD incidence. In multivariate analysis, only VAI was significantly associated with CVD incidence. Regarding CVD mortality, only VAI in the multivariate analysis revealed a significant association. Interestingly, Both VAI and LAP were negatively associated with all-cause mortality. ROC curve analysis indicated the superior performance of LAP and VAI for predicting CVD incidence compared to BMI; however, BMI was better in predicting all-cause mortality. Conclusion: Compared to BMI, LAP and VAI have better predictive performance for the incidence of CVD. In contrast, BMI was superior to VAI and LAP in the prediction of all-cause mortality.

Prevalence of, association with, severity of, and prognostic role of serum hemoglobin level in acutely decompensated heart failure patients.

BACKGROUND: The role of hemoglobin (Hb) level in the short-term prognosis of patients with acute decompensated heart failure (ADHF) remains a matter of debate. We aimed to declare the prevalence of, association with, severity of, and prognostic role of SHL with ADHF. METHODS: Using the data from the Persian Registry Of Cardiovascular Disease/ Heart Failure (PROVE-HF) study, we assessed the association between anemia and polycythemia (Hb < 13 g/dLit, > 16.5 g/dLit in males and < 12 g/dLit, and > 16 g/dLit in females, respectively) and short-term mortality using Cox proportional hazard modeling, with adjustment of clinically relevant variables. RESULTS: Of 3652 ADHF patients, anemia was seen in 1673 patients (48.40%). The prevalence of mild, moderate, and severe anemia was 42.33% (n = 1546), 3.23% (n = 118), and 0.24% (n = 9), respectively. Also, 422 patients (11.55%) had polycythemia. Compared to non-anemic patients, anemic patients were mainly male, older, and were more likely to have diabetes mellitus (DM), renal dysfunction, hypertension (HTN), and thyroid disease. Significant predictors of short-term mortality were lower systolic and diastolic blood pressure, lower Hb level, and higher blood urea nitrogen (BUN). Anemic patients had higher all-cause mortality [adjusted hazard ratio (aHR) 1.213, 95% confidence interval [CI] 1.054-1.396]. Moderate anemia increased mortality by approximately 80% in males (aHR 1.793, 95% CI 1.308-2.458) and females (aHR 1.790, 95% CI 1.312-2.442), respectively. Polycythemia had no association with short-term mortality in both genders (P-value > 0.05). CONCLUSIONS: This study revealed that anemia is an adverse prognostic factor for short-term mortality in ADHF patients, with higher mortality in moderately anemic patients.

Demographic, Life Style and Job-Related Determinants of Quality of Life of Industrial Manufacturing Employees: An Application of Multilevel Latent Class Regression on a Large Cross-Sectional Study.

BACKGROUND: Employees are one of the key elements of an organization and measure the quality of life (QoL) provides reliable assessment of health and wellbeing in this population. This study aimed at investigating the QoL in a large sample of Iranian industrial manufacturing employees and its determinants. METHODS: In a cross-sectional study conducted was in 2015, 3063 people were selected among 16000 Esfahan Seal Company's employees using multistage cluster sampling. QoL was evaluated by EQ-5D questionnaire, mental health by GHQ-12, physical activity by IPAQ, job stress by Effort-Reward Imbalance questionnaire. Self-report questionnaire was used for gathering demographic characteristics. Multilevel latent class regression analysis was used for data analysis using R (3.4.3). RESULTS: The mean (SD) age of the study participants was 36.74 (7.31), and 91.5% of them were males. The mean (SD) sleep duration was 7.11 (1.17), and 95.4% of the participants had normal mental health. Latent class analysis classified employees into two classes (high (82.4%) and low QoL (17.6%)). Also employees' job categories classified into high and low QoL classes (79.55% and 20.45%, respectively). Latent class regression showed that lower age (OR=0.93; P< 0.0001), being male (OR=1.75; p=0.009), lower levels of education (OR=2.1; P< 0.0001), normal mental health (OR=12.4; P< 0.0001), higher sleep duration (OR=1.2; P< 0.0001) and lower BMI (OR=0.96; P=0.016) were significant predictors of being in high QoL class. CONCLUSION: Our study provides data about the QoL of industrial manufacturing employees along with its significant determinants. The findings picture the ways for improving QoL, finally increasing the efficiency and productivity of workforce by directing health policies appropriately.

Association between shift work and obesity in a large sample of Iranian steel industry workers.

Obesity is associated with several chronic diseases, and previous research suggests that shift work could be associated with the risk of overweight and obesity, but the results remain inconclusive. Furthermore, only a few studies report related findings for industrial workforce with high job-related stress. The aim of this cross-sectional study was to see if such association exists in a large sample of 3063 industrial workers in a developing country. The sample was selected among 16,000 steel company workers through multistage cluster sampling. We took anthropometric measurements, including body mass index (BMI), waist circumference (WC), and waist-to-hip ratio (WHR). Information about potential confounders was collected with a self-administered questionnaire. The association between shift work and both general and abdominal obesity was established with multinomial and binary logistic regression analysis. The study sample consisted of 1683 (54.9 %) rotational shift workers and 1380 (45.1 %) day workers. Shift work was significantly associated with higher risk of overweight after adjusting for the impacts of potential confounders (OR=1.2; 95 % CI:1.04-1.4) but not with abdominal obesity. This study established that shift work was an independent risk factor for overweight in industrial shift workers. Modification of working schedules is recommended, particularly for prolonged, continuous shift work.

Demographic, life style and job-related determinants of quality of life of industrial manufacturing employees: an application of multilevel latent class regression on a large cross-sectional study

BACKGROUND: Employees are one of the key elements of an organization and measure the quality of life (QoL) provides reliable assessment of health and wellbeing in this population. This study aimed at investigating the QoL in a large sample of Iranian industrial manufacturing employees and its determinants. METHODS: In a cross-sectional study conducted was in 2015, 3063 people were selected among 16000 Esfahan Seal Company's employees using multistage cluster sampling. QoL was evaluated by EQ-5D questionnaire, mental health by GHQ-12, physical activity by IPAQ, job stress by Effort­Reward Imbalance questionnaire. Self-report questionnaire was used for gathering demographic characteristics. Multilevel latent class regression analysis was used for data analysis using R (3.4.3). RESULTS: The mean (SD) age of the study participants was 36.74 (7.31), and 91.5% of them were males. The mean (SD) sleep duration was 7.11 (1.17), and 95.4% of the participants had normal mental health. Latent class analysis classified employees into two classes (high (82.4%) and low QoL (17.6%)). Also employees' job categories classified into high and low QoL classes (79.55% and 20.45%, respectively). Latent class regression showed that lower age (OR=0.93; P< 0.0001), being male (OR=1.75; p=0.009), lower levels of education (OR=2.1; P< 0.0001), normal mental health (OR=12.4; P< 0.0001), higher sleep duration (OR=1.2; P< 0.0001) and lower BMI (OR=0.96; P=0.016) were significant predictors of being in high QoL class. CONCLUSION: Our study provides data about the QoL of industrial manufacturing employees along with its significant determinants. The findings picture the ways for improving QoL, finally increasing the efficiency and productivity of workforce by directing health policies appropriately