Association between dietary inflammatory index and risk of cardiovascular disease in the Mashhad stroke and heart atherosclerotic disorder study population.

The dietary inflammatory index (DII) is a novel way of describing diet that has been studied in relation to various health conditions, including cardiovascular disease (CVD) in several populations. We aimed to investigate the association between DII and CVD events among a representative population sample in northeastern Iran. This prospective cohort study was a subsample of 4,672 adults aged 35-65 years, and recruited as part of Mashhad stroke and heart atherosclerotic disorder cohort study population. The DII was computed at baseline according to a 65-item validated food frequency questionnaire. Cox regression was used to determine the association of DII with incident CVD. One hundred twenty-four participants developed CVD (including 24 cases of myocardial infarction [MI], 34 cases of stable angina [SA], and 66 cases of unstable angina [UA]). After adjusting for potential confounding factors, a hazard ratios of 1.06 (95% confidence interval: 0.70-1.60), 1.36 (95% confidence interval: 0.52-3.52), 1.33 (95% confidence interval: 0.60-2.94), and 0.86 (95% confidence interval: 0.48-1.53) were found for total CVD, MI, SA, and UA events, respectively, among the participants with proinflammatory diet (DII ≥ 0) versus those with anti-inflammatory diet (DII < 0). There was no statistically significant association between the DII and total CVD, MI, SA, or UA in this population of middle-aged Iranian men and women.

Type 2 diabetes, but not obesity, prevalence is positively associated with ambient temperature.

Cold exposure stimulates energy expenditure and glucose disposal. If these factors play a significant role in whole body energy balance, and glucose homeostasis, it is predicted that both obesity and type 2 diabetes prevalence would be lower where it is colder. Previous studies have noted connections between ambient temperature and obesity, but the direction of the effect is confused. No previous studies have explored the link of type 2 diabetes to ambient temperature. We used county level data for obesity and diabetes prevalence across the mainland USA and matched this to county level ambient temperature data. Average ambient temperature explained 5.7% of the spatial variation in obesity and 29.6% of the spatial variation in type 2 diabetes prevalence. Correcting the type 2 diabetes data for the effect of obesity reduced the explained variation to 26.8%. Even when correcting for obesity, poverty and race, ambient temperature explained 12.4% of the variation in the prevalence of type 2 diabetes, and this significant effect remained when latitude was entered into the model as a predictor. When obesity prevalence was corrected for poverty and race the significant effect of temperature disappeared. Enhancing energy expenditure by cold exposure will likely not impact obesity significantly, but may be useful to combat type 2 diabetes.