Cardiovascular Disease Risk Factors and Cognitive Impairment
ABSTRACT The role of cardiovascular disease risk factors in the occurrence and progression of cognitive impairment has been the subject of a significant number of publications but has not achieved widespread recognition among many physicians and educated laymen. It is apparent that the active treatment of certain of these cardiovascular disease risk factors is accompanied by a reduced risk for cognitive impairment. Patients with hypertension who are treated experience fewer cardiovascular disease events as well as less cognitive impairment than similar untreated patients. Patients who exercise may present with less cognitive impairment, and obesity may increase the risk for cognitive impairment. Lipid abnormalities and genetic markers are associated with an increased risk for cardiovascular disease and cognitive impairment. Autopsy studies have demonstrated a correlation between elevated levels of cholesterol and amyloid deposition in the brain. Research has demonstrated a relation between atherosclerotic obstruction lesions in the circle of Willis and dementia. Diabetes mellitus is associated with an increased risk for cardiovascular disease and cognitive impairment. A number of nonpharmacologic factors have a role in reducing the risk for cognitive impairment. Antioxidants, fatty acids, and micronutrients may have a role, and diets rich in fruits and vegetables and other dietary approaches may improve the outlook for patients considered at risk for cognitive impairment.
- SourceAvailable from: Michihiro Suwa
- "The A1166C polymorphism of AGTR1 has been reported to be associated with increased risks of hypertension , myocardial infarction , and cerebral infarction . There have been no prospective cohort studies in Japanese subjects regarding the association between the polymorphism of the A1166C of AGTR1 and cardiovascular events. "
Dataset: Int J Card:09
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- "The strengths of this study include the following: (a) novelty: this is, to the best of our knowledge, the first study to explore the association between several metabolic and hormonal parameters and mental performance in two experimental conditions—fasting and after breakfast intake; (b) the specific age range: young children have a different brain metabolism than adults or adolescents, which deserves specific investigation; (c) absence of morbidity associated with obesity, such as hypertension, diabetes and dislipidemia , which also affect the brain function (Nash and Fillit, 2006). "
ABSTRACT: Skipping breakfast influences cognitive performance. The aim of our study was to investigate the relationship between the variation of hormonal and metabolic postprandial parameters induced by breakfast consumption or fasting and cognitive performance in obese children. Cross-sectional study for repeated measures. Memory and attention assessment tests, hormones and nutrient oxidation were measured before and after consuming breakfast vs fasting in 10 prepubertal obese children. Fasting induced a significant (P<0.05) increase of the Overall Index of the Continuous Performance Test II (a global index of inattention) and the Test of Memory and Learning Word Selective Reminding (a test of verbal memory), whereas no changes were found after breakfast. Fasting was associated with a reduction of insulin and an increase in glucagon, with no changes in glucose. The increase in inattention was associated with a reduction of carbohydrate oxidation (ρ=-0.66, P<0.05). We found no difference in the area under the curve of peptide YY and glucagon-like peptide-1 after breakfast or fasting, whereas Ghrelin was significantly lower. No association between postprandial hormone variation and cognitive performance was found. Attention and visual memory performance in the morning were reduced when the children skipped breakfast. No association was found with hormones or metabolic changes, but we did find an association with a reduction of carbohydrate oxidation. Nevertheless, these preliminary findings need confirmation in larger sample size.European journal of clinical nutrition 03/2012; 66(3):314-21. DOI:10.1038/ejcn.2011.206 · 2.95 Impact Factor
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- "This is not necessarily justifiable as several conditions like hypertension , atrial fibrillation, hyperlipidemia, diabetes, obesity, and smoking have been associated with cognitive decline in the elderly (Duron and Hanon 2008). Furthermore, some medications have been associated with drug-induced cognitive disorders (Gray et al. 1999) and some others used for the treatment of classical cardiovascular risk factors (CVRF) have a favorable effect on risk factor associated cognitive decline (Haag et al. 2009a; Haag et al. 2009b; Nash and Fillit 2006; Shah et al. 2009). Our intention was to evaluate whether age and cardiovascular risk factors impair comprehension of complex instructions and their practical implementation. "
ABSTRACT: Verbal comprehension is critical to the success of medical counseling. Here, we tested how age and vascular risk factors affect the ability to understand complex instructions. Verbal comprehension, cognitive functions, and vascular risk factors were assessed in 39 mid- and 38 late-life community-dwelling individuals (48 to 59 years and >59 years of age, respectively). To test for verbal comprehension, we used a modified version of the Token Test (TT). In midlife individuals, education (β = 0.572, p < 0.05) was the only predictor for extended-TT performance. In late-life individuals, age (β = -1.015, p < 0.001) and body mass index (β = -0.651, p = 0.003) were significantly correlated with extended-TT performance and explained 50% of the variance in extended-TT performance (adjusted R (2) = 0.503). This relation is only partly explained by conventional neuropsychological measures as the ones used in our test battery. These results indicate that aging and overweight impair comprehension of complex instructions. Therefore, medical counseling appropriate for midlife individuals may be less successful in elderly people and particularly in those with metabolic disturbances.Age 03/2011; 33(1):101-6. DOI:10.1007/s11357-010-9161-9 · 3.45 Impact Factor