Aim Obesity is an emerging public health problem, with its incidence on the rise. An abnormal metabolic profile is a risk factor for developing obesity. Dietary factors play a central role in the regulation of inflammation and obesity. The aim of the present study was to determine the prevalence of metabolically healthy obese and metabolically unhealthy obese (MUO) phenotypes, and their association with dietary inflammatory index (DII) among obese Iranian people. Methods A cross‐sectional study was conducted from July to October 2017 among 300 obese participants in southern Tehran. DII scores were computed based on the overall inflammatory properties of 32 dietary components using dietary intake assessed by food frequency questionnaire. MUO phenotype was defined as having three or more of these metabolic abnormalities: high blood glucose, high triglycerides, low high‐density lipoprotein cholesterol, elevated blood pressure or abdominal obesity. The association was determined using logistic regression analysis. Results The MUO phenotype (n = 176) was found in 63.5% of obese participants. Compared with participants in the first quartile, those in the fourth quartile of DII score (more pro‐inflammatory diet) had higher odds of MUO phenotype (odds ratio, OR: 2.58 (95% CI: 1.19–5.59), P = 0.04), and there was a significant association between the continuous form of DII score and the odds of MUO phenotype (OR: 1.18 (95% CI: 1.01–1.37)) after adjusting for potential confounders. Conclusions Higher DII scores were positively associated with the MUO phenotype. A more pro‐inflammatory diet is a potential risk factor for MUO phenotype.

We aimed to evaluate the effect of saffron (Crocus Sativus L.) treatment on endurance capacity, mitochondrial biogenesis, inflammation, antioxidant, and metabolic biomarkers in Wistar rats. Forty male rats were allocated equally into four groups: Saffron, Exercise and Saffron, Exercise and Placebo, and Placebo. Endurance training was accomplished on a specified rodent motor‐driven treadmill. Running to fatigue test and also metabolic and molecular indices were measured after eight weeks of intervention. mtDNA copy number and NRF‐1 gene expression increased significantly in the Ex + S group compared to the exercised and control group (p < 0.05). Endurance capacity time increased in the Ex + S group compared to the Ex group (p < 0.05). Malondialdehyde, CPK, AST, and IL‐6 decreased and antioxidant parameters including Glutathione peroxidase and Glutathione increased in the Ex + S group compared to exercised rats (p < 0.01). Saffron enhanced mitochondrial biogenesis, decreased oxidative stress, inflammation, and modulated metabolic biomarkers in exercised rats. Practical applications The influence of potential nutrient factors on exercise performance has reached much attention in recent years. Athletes require an appropriate sport supplement to reimburse their fatigue and improve their resilience. Saffron (Crocus Sativus L.) is a well‐known spice in the food trade which is quite popular around the world by giving a desirable taste to food. In an experimental study, we showed that saffron extract treatment during endurance training could improve endurance capacity by modulating several metabolic and genomic factors. Therefore, by relying on the results of this study and the positive effects of saffron published in previous studies, saffron could be added to sport beverages and supplements to enhance an athlete's performance.

BackgroundGastrointestinal (GI) tract cancer is one of the common causes of the mortality due to cancer in most developing countries such as Iran. The digestive tract is the major organ involved in the cancer. The northern part of the country, surrounded the Caspian Sea coast, is well known and the region with highest regional incidence of the GI tract cancer. In this paper our aim is to study the most common risk factors affecting the survival of the patients suffering from GI tract cancer using parametric models with frailty.MethodsThis research was a prospective study. Information of 484 cases with GI cancer was collected from Babol Cancer Registration Center during 1990-1991. The risk factors we studied are age, sex, family history of cancer, marital status, smoking status, occupation, race, medication status, education, residence (urban, rural), type of cancer, migration status (indigenous, non-native). The studied cases were followed up until 2006 for 15 years. Hazard ratio was used to interpret the death risk. The effect of the factors in the study on the patients survival are studied under a family of parametric models including Weibull, Exponential, Log-normal, and the Log-logistic model. The models are fitted using with and without frailty. The Akaike information criterion (AIC) was considered to compare between competing models.ResultsOut of 484 patients in the study, 321 (66.3%) were males and 163 (33.7%) were females. The average age of the patient at the time of the diagnosis was 59 yr and 55 yr for the males and females respectively. Furthermore, 359 (74.2%) patients suffered from esophageal, 110 (22.7%) patients recognized with gastric, and 15 (3.1%) patients with colon cancer. Survival rates after 1, 3, and 5 years of the diagnosis were 24%, 16%, and 15%, respectively. We found that the family history of the cancer is a significant factor on the death risk under all statistical models in the study. The comparison of AIC using the Cox and parametric models showed that the overall fitting was improved under parametric models (with and without frailty). Among parametric models, we found better performance for the log-logistic model with gamma frailty than the others. Using this model, gender and the family history of the cancer were found as significant predictors.ConclusionsResults suggested that the early preventative care for patients with family history of the cancer may decrease the risk of the death in the patients with GI cancer. The gender appeared to be an important factor as well so that men experiencing lower risk of death than the women in the study. Since the proportionality assumption of the Cox model was not held (p = 0.0014), the Cox regression model was not an appropriate choice for analysing our data.

No abstract

No abstract