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There are actually some preliminary surgeries going on right now where doctors are more less injecting stem cells behind the retina to slow down the loss of vision in Age-related macular degeneration which actual works very similar to diabetic retinopathy which is the diabetes cause blindness. Most kids are regularly vaccinated(because their immune system can’t handle it on their own as well).
In another article in the same issue of the journal Deneen Vojta chief clinical officer for the UnitedHealth Diabetes Prevention and Control Alliance reviewed different strategies that may help stem the rising tide of type 2 diabetes.
I glanced down and saw 3 muffin wrappers from the hospital cafeteria in the trash can and a corndog stick. For super-novice something like cycling through Holland like from Hoek van Holland to Amsterdam is fun.
That said your story wasn’t perfectly clear about whether the pig was dead or not but it seems dead because keeping a live adult pig in a pickup would be a trick. ICD-10-CM codes do not require an additional fifth digit to food diet for diabetes identify the type of meals ideas for diabetics diabetes mellitus Cooking Diabetes Type 2 and whether the diabetes is controlled or uncontrolled. The first year was hard but I was determined to get to know as much as I could about Type 2 diabetes. If you think you may have type 2 make a Dr appt and be check!!  I had 5 out of these 7 symptoms and I was still stubborn going in.  It took 3 extra months of feeling horrible but I really did think I was ill because of my sick new born. Dedicated to:I dedicate my "Get Up and Get Moving'" web site to my dear mother in-law Sharon Knapp who I miss so much.
This Concept Map, created with IHMC CmapTools, has information related to: Diabetes Mellitus-Type 2, DB 63 year old male. Science, Technology and Medicine open access publisher.Publish, read and share novel research.
Age is an Important Risk Factor For Type 2 Diabetes Mellitus and Cardiovascular DiseasesKetut Suastika1, Pande Dwipayana1, Made Siswadi Semadi1 and RA Tuty Kuswardhani2[1] Division of Endocrinology and Metabolism, Internal Medicine, Faculty of Medicine, Udayana University, Sanglah Hospital, Denpasar, Indonesia[2] Division of Geriatrics; Department of Internal Medicine, Faculty of Medicine, Udayana University, Sanglah Hospital, Denpasar, Indonesia1. Akbaraly TN, Kivimaki M, Ancelin ML, Barberger-Gateau P, Mura T, Tzourio C, Touchon J, Ritchie K, Berr C.
Hayashi T, Kawashima S, Itoh H, Yamada N, Sone H, Watanabe H, Hattori Y, Ohrui T, Yokote K, Nomura H, Umegaki H, Iguchi A; Japan CDM Group. Holvoet P, Kritchevsky SB, Tracy RP, Mertens A, Rubin SM, Butler J, Goodpaster B, Harris TB. Kirwan JP, Khrisnan RK, Weaver JA, Del Aguila LF, Evans WJ.Human aging is associated with altered TNF-a production during hyperglycemia and hyperinsulinemia. Minamino T, Orimo M, Shimizu I, Kunieda T, Yokoyama M, Ito T, Nojima A, Nabetani A, Oike Y, Matsubara H, Ishikawa F, Komuro I. Poehlman ET, Berke EM, MI Joseph JR, Gardner AW, Ades PA, Katzan-Rook SR, Goran MI.Influence of aerobic capacity, body composition, and thyroid hormone on age-related decline in resting metabolic rate. Cases with risk haplotype develop type 2 diabetes younger and at a lower BMI than non-carriers. Extended Data Figure 5: Cases with risk haplotype develop type 2 diabetes younger and at a lower BMI than non-carriers.
Program in Medical and Population Genetics, Broad Institute of Harvard and MIT, Cambridge, Massachusetts 02142, USA. Centro de Estudios en Diabetes, Unidad de Investigacion en Diabetes y Riesgo Cardiovascular, Centro de Investigacion en Salud Poblacional, Instituto Nacional de Salud Publica, 01120 Mexico City, Mexico. Center for Human Genetic Research and Diabetes Research Center (Diabetes Unit), Massachusetts General Hospital, Boston 02114, Massachusetts, USA. Department of Preventive Medicine, Keck School of Medicine, University of Southern California, Los Angeles, California 90089, USA.
Center for Human Genetic Research, Massachusetts General Hospital, Boston, Massachusetts 02114, USA. Department of Biology, Massachusetts Institute of Technology, Cambridge, Massachusetts 02139, USA. Analytic and Translational Genetics Unit, Massachusetts General Hospital, Boston, Massachusetts 02114, USA. The Genomics Platform, The Broad Institute of Harvard and MIT, Cambridge, Massachusetts 02142, USA.
Department of Evolutionary Genetics, Max Planck Institute for Evolutionary Anthropology, D-04103 Leipzig, Germany. Palaeolithic Department, Institute of Archaeology and Ethnography, Russian Academy of Sciences, Siberian Branch, 630090 Novosibirsk, Russia. The Metabolite Profiling Platform, The Broad Institute of Harvard and MIT, Cambridge, Massachusetts 02142, USA. Cancer Biology Program, The Broad Institute of Harvard and MIT, Cambridge, Massachusetts 02142, USA.
Duke National University of Singapore Graduate Medical School, Singapore 169857, Singapore.
Saw Swee Hock School of Public Health, National University of Singapore, Singapore 117597, Singapore.
Department of Medicine, Yong Loo Lin School of Medicine, National University of Singapore, Singapore 117597, Singapore. Department of Biostatistics, Center for Statistical Genetics, University of Michigan, Ann Arbor, Michigan 48109, USA.
Department of Medicine, Department of Genetics, Albert Einstein College of Medicine, Bronx, New York 10461, USA. Department of Genetics, Texas Biomedical Research Institute, San Antonio, Texas 78227, USA. Center for Genomics and Personalized Medicine Research, Center for Diabetes Research, Department of Biochemistry, Department of Internal Medicine, Wake Forest School of Medicine, Winston-Salem, North Carolina 27157, USA. Department of Biomedical Science, Hallym University, Chuncheon, Gangwon-do, 200-702 South Korea.
Endocrinology and Metabolism Service, Hadassah-Hebrew University Medical School, Jerusalem 91120, Israel.
Human Genetics Center, University of Texas Health Science Center at Houston, Houston, Texas 77030, USA. National Heart and Lung Institute (NHLI), Imperial College London, Hammersmith Hospital, London W12 0HS, UK.
Department of Medicine, University of Eastern Finland, Kuopio Campus and Kuopio University Hospital, FI-70211 Kuopio, Finland. Center for Genome Science, Korea National Institute of Health, Osong Health Technology Administration Complex, Chungcheongbuk-do 363-951, South Korea.
Department of Epidemiology and Public Health, National University of Singapore, Singapore 117597, Singapore. Centre for Molecular Epidemiology, National University of Singapore, Singapore 117456, Singapore. Genome Institute of Singapore, Agency for Science, Technology and Research, Singapore 138672, Singapore. Graduate School for Integrative Science and Engineering, National University of Singapore, Singapore 117456, Singapore. Department of Statistics and Applied Probability, National University of Singapore, Singapore 117546, Singapore.
Department of Physiology and Biophysics, University of Mississippi Medical Center, Jackson, Mississippi 39216, USA. Division of Nephrology, Department of Medicine, University of Texas Health Science Center at San Antonio, San Antonio, Texas 78229, USA.
Division of Diabetes, Department of Medicine, University of Texas Health Science Center at San Antonio, San Antonio, Texas 78229, USA.
Division of Clinical Epidemiology, Department of Medicine, University of Texas Health Science Center at San Antonio, San Antonio, Texas 78229, USA.
See the author list for details of author contributions.A list of participants and affiliations for the T2D-GENES Consortium and the Broad Genomics Platform is available in the Supplementary Information.
Extended Data Figure 1: Principal component analysis (PCA) projection of SIGMA samples onto principal components calculated using data from samples collected by the Human Genome Diversity Project (HGDP) and 1000 Genomes Project. Point colour indicates r2 to the most strongly associated site (rs7903146) and recombination rate is also shown, both based on the 1000 Genomes ASN population. Extended Data Figure 4: Regional plots for SLC16A11 conditional on associated missense variants of that gene. Extended Data Figure 6: Frequency distribution of the risk haplotype and dendrogram depicting clustering with Neanderthal haplotypes. If they test HIV negative they have not been infected and have no further risk of becoming HIV positive from the pre-natal contact. Diseases caused by inadequate sleep include Type 2 Diabetes heart disease depression mood swings For now consuming kiwi fruit one hour before sleep not only provides needed vitamin C and fiber: it may just help you sleep better. As a member of the Living Well with Diabetes program you can: Automatically receive delicious recipes through our e-newsletters.
Energizer Bunny; I also have type 2 diabetes and yes you can get it under control with diet and exercise. I public speak on the subject and motivate others to make healthy lifestyle changes.  I speak to newly diagnosed diabetics who have many concerns and help them rid of their fears and get them feeling empowered!!  I love life and being a diabetic has added blessings to my life!!  YEP!! Now I know different and I want everyone to be tested if they have any of these symptoms.  The sooner you know the sooner you can get treatment and the sooner you will start feeling better. 5 foot 8 inches, 230 pound man with Type 2 diabetes mellitus for 7 years Fasting blood sugar  Range averages 110-150 ???? Frequency of metabolic syndrome (MS), impaired fasting glycemia (IFG), and diabetes mellitus (DM) in the younger-aged and elderly.


IntroductionA field study by World Health Organization (WHO), World Bank and Harvard University in 1990 found a changing pattern of diseases caused by unhealthy lifestyle changes that may eventually lead to metabolic syndrome, type 2 diabetes mellitus, coronary arterial diseases, depression, and traffic accidents (Kinsella and Phillips, 2005).
Low HDL cholesterol is associated with the risk of stroke in elderly diabetic individuals: changes in the risk for atherosclerotic diseases at various ages. The metabolic syndrome, circulating oxidized LDL, and risk of myocardial infarction in well-functioning elderly people in the health, aging, and body composition cohort. High liporotein (a) level promotes both coronary atherosclerosis and myocardial infarction: a path analysis using a large number of autosy cases.
Point colour indicates r2 to the most strongly associated SNP (rs13342232) and recombination rate is also shown, both based on the 1000 Genomes ASN population. Sample size for each tissue (n): adipose (394), adrenal (69), brain (1,990), breast (4,104), heart (178), kidney (675), liver (721), lung (1,442), pancreas (150), placenta (107), prostate (578), salivary gland (26), skeletal muscle (793), skin (947), testis (102), thyroid (108).
Cooking Diabetes Type 2 your post finely illustrates why professionals need to stick to their area of expertise.
You should be careful not to eat anything that can personal diabetes treatment plan increase your sugar level.
It really has!!  So today I celebrate the 10 yrs I have had diabetes and I celebrate being a diabetic!!  LIFE IS GOOD!!!!
Thank you for teaching me it takes courage to change and most of all thank you for teaching me that it is only through being your true self you will find happiness. The study also predicted that cerebrovascular diseases would become the most prevalent disease, whereas human HIV infection would sharply increase in the year 2020 (Kinsella and Phillips, 2005). P values from two-sample t-test between type 2 diabetes risk haplotype carriers and type 2 diabetes non-carriers.
A list of sample identities and accession numbers are available in the Supplementary Information. Point colour indicates r2 to rs11564732 and recombination rate is also shown, both based on the 1000 Genomes ASN population. Nodes for modern human haplotypes are labelled in red or blue with the 1000 Genomes population in which the corresponding haplotype resides. Excessive thirst: This happens as the body attempts to replace fluids lost as a result of excessive urination. The cynic in me wonders if the cafeteria vendor lobbied to get this passed so they could increase their customer base. The lifestyle-related and degenerative diseases are significant problems in the old aged population group.The number of elderly population has increased worldwide, and recently it has been increasing sharply in the developing countries. Elliott, Metabolic alterations in middle-aged and elderly obese patients with type 2 diabetes.
Archaic Neanderthal sequences are labelled in black and include the low-coverage Neanderthal sequence14 (labelled Vindija), and the unpublished Neanderthal sequence that is homozygous for the 5 SNP risk haplotype17 (Altai). Anorexics anorexigenics or appetite suppressants are substances (dietary supplements or drugs) that carbohydrates so reduces the abnormally high blood sugar levels that occur after each meal hence it has been prescribed for pregnancy and diabetes type 2 treatment treatment of diabetes. The foundation of modern medicine and prescriptions is rooted in traditional medicine which includes using herbs to fight ailments and disease.
The diabetic food pyramid is different than the typical Food Guide Pyramid in that it recommends foods based on carbohydrates and proteins rather than on calories and fats. Occupational Therapy and Diabetes: Understanding our Role in Chronic CareManagement Occupational Therapy Association of California Annual Conference have given birth to a baby that is more than 4 kg (9 lbs). The projection of the number of elderly population in Indonesia by the year 2010 is 23,992.
Suastika, Age and homocystein were risk factor for peripheral arterial disease in elderly with type 2 diabetes mellitus.
H1 includes haplotypes from MXL and FIN, and H2 and H3 both include haplotypes from CLM, MXL, CHB and ASW. On the basis of negative controls, a normalized log2 expression of 4 is considered baseline and log2 expression values greater than 6 are considered expressed. Both films totally immersed me in their world and in film that is all you can ask abbott diabetes control for life for.
So if you have diabetes there are a few simple things you can do to help manage your condition. The Indonesian Central Bureau for Statistics (Badan Pusat Statistik) has reported that Indonesia is the world’s fourth in the number of elderly population after China, India, and USA (Komala et al., 2005). Modern human sequences included are all 1000 Genomes Phase I samples that are homozygous for the 5 SNP risk haplotype (n = 15), and 16 non-risk haplotypes—four haplotypes (from two randomly selected individuals) from each of the CLM (Colombian in Medellin, Colombia), MXL (Mexican Ancestry in Los Angeles, California), CHB (Han Chinese in Beijing, China) and FIN (Finnish in Finland) 1000 Genomes populations (the populations with carriers of the 5 SNP haplotype). But yeah if there is any sort of line Cooking Diabetes Type 2 there its a negative my friend.
US Bureau of Census predicted that from 1990 to 2020, the Indonesian elderly population would increase to 41.4%. The red subtree depicts the Neanderthal clade, with all risk haplotypes clustering with the Altai and Vindija sequences. Diabetes (also called Adult onset diabetes or Non-insulin dependent diabetes) is a disease in which your blood glucose or sugar levels are too high.
The predicted increased number of elderly was ascribed to the success of health promotion and improvement of social and economic status (Kinsella and Taeuber, 1993).
Metabolic disorders including type 2 diabetes mellitus (T2DM) and cardiovascular diseases are closely related with the aging process.
Nemeth, Histochemical and enzymatic comparison of the gastrocnemius muscle of young and elderly men and women.J. The dendrogram was generated by the R function hclust using a complete linkage clustering algorithm on a distance matrix measuring the fraction of SNPs called in the 1000 Genomes project at which a pair of haplotypes differs (the y axis represents this distance). Central obesity and insulin resistance as the initial preconditions and its consequences related to metabolic diseases and cardiovascular diseases are frequently found among the elderly.
Donath, Aging correlates with decreased ?-cell proliferative capacity and enhanced sensitivity to apoptosis. Because haplotypes are unavailable for the archaic samples, we picked a random allele to compute the distance matrix.
Decline in lean body mass and increase in body fat, particularly visceral adiposity that often accompanies aging, may contribute to the development of insulin resistance.
Bolli, Demonstration of a critical role for free fatty acids in mediating counter regulatory stimulation of gluconeogenesis and suppression of glucoseutilization in humans. As for the mechanism of T2DM, it is known that aging induces a decrease of insulin sensitivity and alteration or insufficient compensation of beta cell functional mass in the face of increasing insulin resistance (Meneilly and Elliot, 1999).
Ducimetiere, The metabolic syndrome and the carotid artery structure in non-institutionalized elderly subjects. Related to beta cell functions, aging correlates with a decrease of beta cell proliferation capacity and enhances sensitivity to apoptosis (Maedler et al., 2006). Young, Effect of age on energy expenditure and substrate oxidation during experimental overfeeding in healthy men.
It has recently been proposed that an age-associated decline in mitochondrial function contributes to insulin resistance in the elderly (Petersen et al., 2003). Lima, Age-related left ventricular remodeling and associated risk for cardiovascular outcomes. Gerich, Effect of aging on glucose homeostasis: Accelerated deterioration of ?-cell function in individuals with impaired glucose tolerance. Lamb, The ageing male heart: myocardial triglyceride content as independent predictor of diastolic function. Age, mitochondrial dysfunction and inflammationMitochondria, a membrane-enclosed organelle found in most eukaryotic cells, generate most of the cell's supply of adenosine triphosphate (ATP), are used as a source of chemical energy, and are involved in a range of other processes such as signaling, cellular differentiation, cell death, as well as the control of the cell cycle and cell growth. Mitochondria have been implicated in several human diseases, including mitochondrial disorders, aging process and cardiac dysfunction. Mitochondrial dysfunction is central to the theories of aging because age-related changes of mitochondria are likely to impair a host of cellular physiological functions in parallel and thus contribute to the development of all the common age-related diseases (Dai et al., 2012). Rising cellular oxidative stress due to any cause induces mtDNA and mitochondria damage and culminates in a mitochondria function crisis, cell death and aging. Otherwise, aging itself causes abnormal mitochondrial morphology and cell death or apoptosis (Seo et al., 2010). How old age can be a major risk factor for CVD via mitochondrial dysfunction has been completely reviewed by Dai et al. The role of NF-?B in bridging the explanation of how aging is associated with inflammation and endothelial dysfunction is reviewed well by Csiszar et al. Another study has shown that depletion of cellular (GSH) during aging plays an important role in regulating the hepatic response to IL-1? (Rutkute et al., 2007). At rest, skeletal muscles of elderly people showed a lower number of macrophages, higher gene expression of several cytokines, and activation of stress signaling proteins, compared with skeletal muscles of young people (Peake et al., 2010). Human aging is associated with the development of insulin resistance, ?-cell dysfunction and glucose intolerance. The level of suppression of the TNF-? production was observed and found to be significantly correlated with insulin action. Reduced suppression of TNF-? production in the elderly may in part contribute to the decline in insulin sensitivity (Kirwan et al., 2001).
Age and lipid metabolismAging and age are often associated with lipid metabolism disorders.
After the age of 20 years, low-density lipoprotein cholesterol (LDL-C) increases significantly in both men and women. LDL-C does not increase or is in a flat state between the age of 50-60 years (male) and 60-70 years (female) (Gobal and Mehta, 2010).


On the other hand, high–density lipoprotein cholesterol (HDL-C) levels decrease during puberty to young adulthood (in males). Throughout their lives women have lower total cholesterol compared to men, but the levels will rise sharply after menopause and will be higher in the age >60 years as compared to men.
Concentrations of triglyceride (TG) increase sharply in males, reaching a peak at the age 40-50 years and decline gradually thereafter.
TG levels increase in women throughout their lives, especially in women taking estrogen replacement therapy (Gobal and Mehta, 2010). With the increase of age the composition of body fat also increases, which especially accumulates in the abdomen triggering the incidence of central obesity.
TG composition in the muscle and liver are higher in older age compared with younger age groups (Cree et al., 2004).
Increased body fat composition is associated with reduced fat oxidation both at rest and in activity (Nagy et al., 1996). Aging (age) affects the release of fatty acids (FFA),from fat tissue (adipose), and the capacity of peripheral tissues such as muscles, to oxidize fat. These are some of the changes in lipid metabolism influenced by age and aging, which decreases lipolysis response and capacity of fat oxidation.Lipolysis is modulated by various hormones such as catecholamines, glucagon, adrenocorticotropic hormone, growth hormone, prostaglandin, and thyroid hormone (Toth and Tchernof, 2000). Decreased ability of catecholamines to stimulate lipolysis in the elderly is caused by decreased fat tissue response to adrenergic stimulation (Dillon et al., 1984). This response involves reduced role of protein kinase A, G-protein complex adenylil cyclase, or the stages in the cyclic AMP signaling cascade (Toth and Tchernof, 2000).
Effects of insulin on plasma FFA was different between in the elderly compared with in younger subjects.
Insulin infusions showed that plasma FFA, turnover and oxidation, and total lipid oxidation were higher significantly in the elderly than in the younger group (Bonadonna et al., 1994). Aging is also associated with decreased sensitivity to antilipolysis effects of insulin (Toth and Tchernof, 2000). In principle, the capacity of metabolically active tissues such as the muscles to oxidize fat represents a combination of the tissue mass and oxidative capacity of the tissue. Fat free mass decreases with age (Poehlman et al., 1992) and in resting condition fat oxidation tends to be influenced by the size of fat free mass itself.
Changes in lipid metabolism in the aging process are associated with dysfunction of endothelial cells pseudocapillarization of the liver sinusoid. This change causes decreased endocytosis, increased leukocyte adhesion, decreased hepatic perfusion and will potentially reduce the passage of chylomicron remnants into hepatocytes (Denke and Grundy, 1990). After activity or after meal, fat oxidation rate is more influenced by the oxidative capacity of muscle tissue. Disposal of non-oxidative free fatty acids into the liver will increase the formation of triglyceride-rich very low-density lipoprotein (VLDL) that plays a role in the formation of atherogenic dyslipidemia. Increased levels of TG and decrease HDL-C are features of atherogenic dyslipidemia in people with central obesity, hypertension and insulin resistance (Linblad et al, 2001). Lower HDL cholesterol is an important risk factor for not only ischemic heart disease but also for cerebrovascular disease, especially in diabetic elderly individuals (Hayashi et al., 2009). Age, insulin resistance and metabolic syndrome Metabolic syndrome is a group of metabolic abnormalities of which central obesity and insulin resistance are believed to be the primary backgrounds. The diagnostic criteria for metabolic syndrome have been proposed by several organizations and associations, all of which are based on five parameters i.e. The pathogenesis of how central obesity causes insulin resistance and metabolic syndrome has been explained in many publications. Decreased insulin sensitivity, reduced muscle mass, and increased body fat mass, especially visceral fat that accompanies aging contribute to insulin resistance in the elderly.
Aging process is also associated with reduced compensatory beta cell mass function of the pancreas and to insulin resistance (Maneilly and Elliott, 1999) as well as with decreased mitochondrial function that contributes to insulin resistance (Petersen et al., 2003).
Insulin resistance as risk factor for cardiovascular disease (CVD) is associated with increase of acute phase protein response and inflammatory markers.
The association of metabolic syndrome and increased frequency of carotid plaque and thickening of the carotid artery intima media in elderly subjects (aged 65-85 years) was noted in a study by Empana et al. Metabolic syndrome in the elderly was associated with two-times increase of CRP levels (3.1 vs. Sports activities >2 hours per week would be effective in lowering the risk of metabolic syndrome.
Age and type 2 diabetes mellitus Similar to metabolic syndrome, the prevalence of impaired fasting glycemia (IFG) and T2DM increase with rising age.
In the United States, the estimated percentage of people aged 20 years or older having diagnosed or undiagnosed diabetes in 2005-2008 was increasing with age.
Similar feature was also observed n England, where the prevalence of diabetes was increasing with age.
There was a tendency of increasing frequency of IFG and T2DM with increasing age (Table 2).
Hypertension, overt proteinuria, IFG and high total cholesterol were independent risk factors for new onset diabetes (Peng et al., 2006). The main factors are that aging induces decrease insulin sensitivity and alteration or insufficient compensation of beta cell functional in the face of increasing insulin resistance (Chang and Halter, 2003). Decrease in beta cell proliferation capacity and enhanced sensitivity to apoptosis are the states related with aging (Maedler et al., 2006). But aging per se has no effect on insulin sensitivity independent of change in body composition. Decline in lean body mass and the increase in body fat particularly visceral adipocytes (“central obesity”) that accompanies aging may contribute to insulin resistance.
It has recently been proposed that an age-associated decline in mitochondrial function contributes to insulin resistance in elderly. Mitochondrial oxidative and phosphorylation function was reduced about 40% in association with increased intramyocellular and intrahepatocellular lipid content and decreased insulin-stimulated glucose uptake (Petersen et al., 2003). The pathophysiological basis of sarcopenia (loss of muscle mass with age) has a relationship with oxidative stress, reduced neuronal stimulation, subclinical inflammatory and insulin resistant state.
Those conditions contribute to the development of glucose intolerance and type 2 diabetes (Khamseh et al., 2011). They also proposed that adipose tissue p53 tumor suppressor mediated the lipid abnormalities and cardiovascular morbidity associated with obesity.
The study found that excessive calorie intake caused accumulation of oxidative stress in the adipose tissue of mice with type 2 diabetes–like disease and promoted senescence-like changes, such as increased activity of senescence-associated ?-galactosidase, increased expression of p53 and increased production of proinflammatory cytokines. Inhibition of p53 activity in adipose tissue decreased the expression of proinflammatory cytokines and improved insulin resistance. Age and cardiovascular diseases Cardiovascular disease remains to be the most important cause of death in all countries over the world. Although certain reports from some developed countries indicate the incidence tends to decrease, from many countries there are reports mentioning that its incidence tends to increase.
Cardiovascular disease is a complex disease; too many risk factors are involved in its pathogenesis. In general, risk factors for CVD can be divided into two main groups, namely traditional and non-traditional risk factors. Age itself may be an independent risk factor or may have other risk factors related to aging or exposure to risk factors during their lifetime. In the United States, CVD was the leading cause of death for persons 65 years of age and over in 2007, which accounted for 28% of deaths in this age group (National Center for Health Statistics, 2011).
Age in the group with CHD (old myocardial infarction and myocardial ischemia) was significantly higher than those without CHD (65.0 vs. This increase includes luminal enlargement with wall thickening and a reduction of elastic properties at the level of large elastic arteries. Long standing arterial pulsation in the central artery has a direct effect on the structural matrix proteins, collagen and elastin in the arterial wall, disrupting muscular attachments and causing elastin fibers to fatigue and fracture.
Increased vascular calcification and endothelial dysfunction is also characteristic of arterial aging.
These changes lead to increased pulse wave velocity, especially along central elastic arteries, and increase in systolic blood pressure and pulse pressure (Lee and Oh, 2010). Aging cardiovascular tissues are exemplified by pathological alterations including hypertrophy, altered left ventricular (LV) diastolic function, and diminished LV systolic reverse capacity, increased arterial stiffness, and impaired endothelial function. This pattern of ventricular remodeling confers significant cardiovascular risk, particularly when present earlier in life.
Peripheral artery disease (PAD), a marker of systemic atherosclerosis, is frequently related with age.
A study by Kuswardhani and Suastika (2010) on elderly patients who visited the Geriatric Outpatient Clinic, Sanglah Hospital showed that diabetic patients with PAD had higher age (70.7 vs. By multivariate analysis (logistic regression), it was found that only age played a role in PAD event. ConclusionThe number of elderly population has increased worldwide, and recently it has been increasing sharply in the developing countries. Prolong survival in the elderly creates an impact on the appearance of metabolic diseases and CVD.



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Comments

  1. Ramal

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    06.03.2016

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    06.03.2016

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    06.03.2016