The TyG index, a simple measure reflecting insulin resistance, might be useful to early identify individuals at a high risk of developing a cardiovascular event.

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: http://links.lww.com/HJH/A620.

Background Whether obesity is a major risk factor for cardiovascular disease in the absence of metabolic comorbidities remains under debate. Indeed, some obese individuals may be at low risk of metabolic-related complications, while normal-weight individuals may not be "healthy." Aims To assess the incidence of ischemic stroke according to the metabolic health and obesity states of 5171 participants from the Vascular-Metabolic CUN cohort. Methods A Cox proportional-hazard analysis was conducted to estimate the hazard ratio and their 95% confidence interval of stroke according to the metabolic health and obesity states based on TyG index and Adult Treatment Panel-III criteria, during 9.1 years of follow-up. Results After 50,056.2 person-years of follow-up, 162 subjects developed an ischemic stroke (incidence rate 3.23 per 1000 person-years). Metabolically healthy obese subjects did not show greater risk of stroke, while metabolically unhealthy participants, obese and non-obese, had an increased risk of stroke, compared with healthy non-obese. The hazard ratios for the multivariable adjusted model were 1.55 (95% CI: 1.36-1.77) and 1.86 (95% CI: 1.57-2.21), respectively. Conclusions Metabolically unhealthy individuals exhibited a greater risk of ischemic stroke than metabolically healthy obese individuals.

We assessed the relationship between a healthy lifestyle and the subsequent risk of developing metabolic syndrome. The “Seguimiento Universidad de Navarra” (SUN) Project is a prospective cohort study, focused on nutrition, lifestyle, and chronic diseases. Participants (n = 10,807, mean age 37 years, 67% women) initially free of metabolic syndrome were followed prospectively for a minimum of 6 years. To evaluate healthy lifestyle, nine habits were used to derive a Healthy Lifestyle Score (HLS): Never smoking, moderate to high physical activity (>20 MET-h/week), Mediterranean diet (≥4/8 adherence points), moderate alcohol consumption (women, 0.1–5.0 g/day; men, 0.1–10.0 g/day), low television exposure (<2 h/day), no binge drinking (≤5 alcoholic drinks at any time), taking a short afternoon nap (<30 min/day), meeting up with friends >1 h/day, and working at least 40 h/week. Metabolic syndrome was defined according to the harmonizing definition. The association between the baseline HLS and metabolic syndrome at follow-up was assessed with multivariable-adjusted logistic regressions. During follow-up, we observed 458 (4.24%) new cases of metabolic syndrome. Participants in the highest category of HLS adherence (7–9 points) enjoyed a significantly reduced risk of developing metabolic syndrome compared to those in the lowest category (0–3 points) (adjusted odds ratio (OR) = 0.66, 95% confidence interval (CI) = 0.47–0.93). Higher adherence to the Healthy Lifestyle Score was associated with a lower risk of developing metabolic syndrome. The HLS may be a simple metabolic health promotion tool.

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Smoking is a serious global public health concern that has been related to many chronic diseases. However, the effect of smoking on eye disorders has been less studied. The aim of this cohort study was to assess the association between current tobacco smokers and the risk of developing glaucoma and furthermore to evaluate the relationship between passive or former smokers and glaucoma.In this prospective and dynamic cohort, 16,797 participants initially who were found not to have glaucoma were followed up for a median of 8.5 years. Validated data on lifestyle, including tobacco consumption, were assessed at baseline. Information about new diagnosis of glaucoma was collected by follow-up questionnaires every 2 years. The outcome was the incidence of self-reported glaucoma during the follow-up. A subsample was used to validate the glaucoma diagnosis.During the 8.5 years of follow-up, 184 new glaucoma cases were identified. Current smokers had a significantly higher risk of glaucoma compared to participants who had never smoked after controlling for potential confounders (Hazard ratio [HR] 1.88 [95% coefficient interval (CI): 1.26–2.81]; P = 0.002). A nonsignificant increased risk was found among former smokers (HR 1.27 [95% CI: 0.88–1.82]; P = 0.198). When we assessed the exposure as per the number of cigarette pack-years, a dose–response relationship between pack-years and the risk of glaucoma was found (HR for the 5th quintile versus the 1st quintile: 1.70 [95% IC: 1.10–2.64], P for trend, 0.009). However, no relationship was found between passive smokers and glaucoma. (HR 0.67 [95% CI: 0.37–1.21]; P = 0.189).Our results suggest a direct association between current smokers and the incidence of glaucoma. In particular, this association was related to the number of pack-years, which was not found in the case of former smokers nor in the case of passive smokers.

The increased risk of diabetes in MHO is attributed to the progression to an unhealthier state. "Healthy obesity" is not a permanent situation but a transitory state.