The cumulative effect of core lifestyle behaviours on the prevalence of hypertension and dyslipidemia

Background: Most cardiovascular disease (CVD) occurs in the presence of traditional risk factors, including hypertension and dyslipidemia, and these in turn are influenced by behavioural factors such as diet and lifestyle. Previous research has identified a group at low risk of CVD based on a cluster of inter-related factors: body mass index (BMI) < 25 Kg/m2, moderate exercise, alcohol intake, non-smoking and a favourable dietary pattern. The objective of this study was to determine whether these factors are associated with a reduced prevalence of hypertension and dyslipidemia in an Irish adult population. Methods: The study was a cross-sectional survey of 1018 men and women sampled from 17 general practices. Participants completed health, lifestyle and food frequency questionnaires and provided fasting blood samples for analysis of glucose and insulin. We defined a low risk group based on the following protective factors: BMI <25 kg/m2; waist-hip ratio (WHR) <0.85 for women and <0.90 for men; never smoking status; participants with medium to high levels of physical activity; light alcohol consumption (3.5–7 units of alcohol/week) and a "prudent" diet. Dietary patterns were assessed by cluster analysis. Results: We found strong significant inverse associations between the number of protective factors and systolic blood pressure, diastolic blood pressure and dyslipidemia. The prevalence odds ratio of hypertension in persons with 1, 2, 3, ≥ 4 protective factors relative to those with none, were 1.0, 0.76, 0.68 and 0.34 (trend p < 0.01). The prevalence odds ratio of dyslipidemia in persons with 1, 2, 3, ≥ 4 protective factors relative to those with none were 0.83, 0.98, 0.49 and 0.24 (trend p = 0.001). Conclusion: Our findings of a strong inverse association between low risk behaviours and two of the traditional risk factors for CVD highlight the importance of 'the causes of the causes' and the potential for behaviour modification in CVD prevention at a population level.

Defining metabolically healthy obesity: role of dietary and lifestyle factors

Background: There is a current lack of consensus on defining metabolically healthy obesity (MHO). Limited data on dietary and lifestyle factors and MHO exist. The aim of this study is to compare the prevalence, dietary factors and lifestyle behaviours of metabolically healthy and unhealthy obese and non-obese subjects according to different metabolic health criteria. Method: Cross-sectional sample of 1,008 men and 1,039 women aged 45-74 years participated in the study. Participants were classified as obese (BMI ≥30kg/m2) and non-obese (BMI <30kg/m2). Metabolic health status was defined using five existing MH definitions based on a range of cardiometabolic abnormalities. Dietary composition and quality, food pyramid servings, physical activity, alcohol and smoking behaviours were examined. Results: The prevalence of MHO varied considerably between definitions (2.2% to 11.9%), was higher among females and generally increased with age. Agreement between MHO classifications was poor. Among the obese, prevalence of MH was 6.8% to 36.6%. Among the non-obese, prevalence of metabolically unhealthy subjects was 21.8% to 87%. Calorie intake, dietary macronutrient composition, physical activity, alcohol and smoking behaviours were similar between the metabolically healthy and unhealthy regardless of BMI. Greater compliance with food pyramid recommendations and higher dietary quality were positively associated with metabolic health in obese (OR 1.45-1.53 unadjusted model) and non-obese subjects (OR 1.37-1.39 unadjusted model), respectively. Physical activity was associated with MHO defined by insulin resistance (OR 1.87, 95% CI 1.19-2.92, p = 0.006).

Investigating the role of Fas (CD95) signalling in the modification of innate immune induced inflammation

Background/Aim: It has been demonstrated that a number of pathologies occur as a result of dysregulation of the immune system. Whilst classically associated with apoptosis, the Fas (CD95) signalling pathway plays a role in inflammation. Studies have demonstrated that Fas activation augments TLR4-mediated MyD88-dependent cytokine production. Studies have also shown that the Fas adapter protein FADD is required for RIG-I-induced IFNβ production. As a similar signalling pathway exists between RIG-I, TLR3 and the MyD88- independent of TLR4, we hypothesised that Fas activation may modulate both TLR3- and TLR4-induced cytokine production. Results: Fas activation reduced poly I:C-induced IFNβ, IL-8, IL-10 and TNFα production whilst augmenting poly I:C-, poly A:U- and Sendai virus-induced IP-10 production. TLR3-, RIG-I- and MDA5-induced IP-10 luciferase activation were inhibited by the Fas adapter protein FADD using overexpression studies. Poly I:C-induced phosphorylation of p-38 and JNK MAPK were reduced by Fas activation. Overexpression of FADD induced AP-1 luciferase activation. Point mutations in the AP-1 binding site enhanced poly I:C-induced IP- 10 production. LPS-induced IL-10, IL-12, IL-8 and TNFα production were enhanced by Fas activation, whilst reducing LPS-induced IFNβ production. Absence of FADD using FADD-/- MEFs resulted in impaired IFNβ production. Overexpression studies using FADD augmented TLR4-, MyD88- and TRIF-induced IFNβ luciferase activation. Overexpression studies also suggested that enhanced TLR4-induced IFNβ production was independent of NFκB activation. Conclusion: Viral-induced IP-10 production is augmented by Fas activation by reducing the phosphorylation of p-38 and JNK MAPKs, modulating AP-1 activation. The Fas adapterprotein FADD is required for TLR4-induced IFNβ production. Studies presented here demonstrate that the Fas signalling pathway can therefore modulate the immune response. Our data demonstrates that this modulatory effect is mediated by its adapter protein FADD, tailoring the immune response by acting as a molecular switch. This ensures the appropriate immune response is mounted, thus preventing an exacerbated immune response.