Correlation between Metabolic Syndrome and Mild Cognitive Impairment
Received: 14-Dec-2017 / Accepted Date: 04-Jan-2018 / Published Date: 11-Jan-2018 DOI: 10.4172/2161-0460.1000414
Abstract
MCI (Mild cognitive impairment) is an intermediate stage in the trajectory from normal cognition to dementia. Subjects with MCI have a high rate of progression to dementia over a relatively short period. Subjects with MCI also experience a greater mortality than cognitively normal subjects.
Method: One hundred and fifty eight patients aged 65 years or more (106 males and 52 females) were included in our study. In addition to a detailed medical and neurological history and examination, MMSE (Mini-Mental State Examination), CDR (Clinical Dementia Rating Scale), Geriatric Depression Scale, Global Deterioration Scale and lipid profile were performed for all patients.
Results: Significant correlation between metabolic syndrome and its components and MCI.
Conclusion: Patients with metabolic syndrome have higher risk for development of MCI.
Keywords: MCI; Metabolic syndrome; Dementia; Risk factors
Introduction
Mild cognitive impairment (MCI) is an etiologically heterogeneous syndrome characterized by memory performance below the normal range, otherwise unimpaired intellectual functioning and well preserved activities of daily living [1]. MCI is a clinical transitional state between the cognitive changes of aging and the earliest clinical features of dementia, a prodromal phase during which slight forgetfulness might be present but other cognitive abilities are preserved [2]. MCI can affect many areas of thought and action such as language, attention, reasoning, judgment, reading and writing. However, the most common variety of MCI causes memory problems [3]. The prevalence of MCI among the population >65 years in developed countries is as high as 10-25% and the annual conversion rate of MCI to AD (Alzheimer`s Disease) has been estimated in general to be about 10-15% [4]. The metabolic syndrome is a clustering of conditions that includes obesity, hypertension, dyslipidemia and impaired glucose metabolism and associated with increase the risk of cardiovascular disease [5]. There is evidence linking the metabolic syndrome with cognitive decline and dementia, but not all studies have found an association [6-8]. Several studies were reported that the risk of developing cognitive impairment increase from 2 to 7 times among those with the metabolic syndrome [9,10]. While hypertension [11], diabetes [12], obesity [13], hypertriglyceridemia [14] and impaired glucose tolerance [15] have each been associated with cognitive impairment, ranging from mild cognitive changes to dementia, the relationship between each metabolic risk factor and cognition is complex [16]. The role of the metabolic syndrome on the rate of cognitive decline remains controversial [17]. Early identification of the people with metabolic syndrome and subsequent treatment of their symptoms could modify or prevent the development of cognitive impairment [18,19]. The study aimed to assess the association between metabolic syndrome and MCI in patients aged ≥ 65 years.
Patients and Methods
The study was carried out on 186 patients aged ≥ 65 years old of both sex attended the outpatient clinic of Medical or Neurology Department of Al-Azhar University Hospitals during the period from May to the end of December 2017. One hundred and fifty eight completed the study and twenty eight patients were dropped because they refuse to complete investigations. This study had been approved by ethical committee of Al-Azhar University Hospitals. Patients who had dementia (MMSE score less than 24 or CDR more than 0.5), cerebrovascular stroke, aphasia or dysphasia, brain tumor, severe head trauma, parkinsonism, premorbid psychiatric illness (schizophrenia, mood disorders and mental retardation), severe sensory impairment (blindness, deafness), drug and alcohol abuse, chronic medical disease (chronic liver disease, renal disease or COPD), or patients who refused to participate in the study were excluded from the study. The patients were divided into two groups, group (A) met criteria for diagnosis of metabolic syndrome and group (B) don’t have metabolic syndrome. All patients included in the study were subjected to complete medical and neurological history regarding to detailed history about age, gender, residence, education level, weight, height, BMI (body mass index), WC (waist circumference), diabetes mellitus, hypertension, smoking, drug or alcohol abuse and family history of dementia. Detailed history of cognitive impairment (onset, duration, course and aggravating factors). Neurological examination including mental state, cranial nerves, motor, sensory systems and cerebellum. Psychometric tests including MMSE, CDR, ADLS (Activities of Daily Living Scale), Geriatric Depression Scale and Global Deterioration Scale were applied for all patients and also some laboratories were done including random blood sugar, HbA1c, serum cholesterol, triglyceride, LDLP (low density), HDLP (high density) lipoproteins, thyroid function and serum uric acid. CT or MRI brain was done for all patients. The statistical analysis was done using the Chi-squared test with the p-Value less than 0.05 considered significant. This analysis was performed using the SPSS-16 Software and the results were tabulated accordingly.
Results
The study was carried out on 156 patients aged ≥ 65 years old of both sex divided into two groups, group (A) met criteria for diagnosis of metabolic syndrome and group (B) don’t have metabolic syndrome. Group A were 73 patients (44 male and 29 female) with mean age 70.68 ± 5.03 years while group B were 85 patients (62 male and 23 female) with mean age 70.9 ± 6.26 years. Regard education level, about 25% of patients were educated while the remaining either not educated or just read and write and also 22% of patients were smoker (Table 1). The frequency of metabolic syndrome component were 55% hypertensive, 47.5% diabetic, 41.1% had central obesity, 45.6% had high serum triglyceride and 56.3% had low serum HDL (Tables 2 and 3).
Variables | Group A (n=73) | Group B (n=85) | Total (n=158) | P value | |||
---|---|---|---|---|---|---|---|
No. | Percent | No. | Percent | No. | Percent | ||
Sex Male Female |
44 29 |
60.27% 39.73% |
62 23 |
73% 27% |
106 52 |
67.1% 32.9% |
`0.064 |
Education level Illiterate Read and write Educated |
30 2914 |
41.1% 39.7%19.2% |
34 2724 |
40% 31.8% 28.2% |
64 5638 |
40.5% 35.4%24.1% |
0.358 |
Smoking | 6 | 8.33% | 29 | 33.7% | 35 | 22.2% | 0.001 |
Age (M ± SD) | 70.68 ± 5.03 | 70.9 ± 6.26 | 70.8 ± 5.64 | 0.55 | |||
BMI (M ± SD) | 28.08 ± 4.28 | 26.56 ± 4.07 | 27.27 ± 4.22 | 0.025 | |||
WC (M ± SD) | 94.95 ± 12.42 | 90.45 ± 12.42 | 92.53 ± 12.58 | 0.025 | |||
MMSE (M ± SD) | 25.74 ± 1.95 | 27.08 ± 1.73 | 26.46 ± 1.95 | 0.001 |
Table 1: Demographic data of the studied patients.
Variables | Group A (n=73) | Group B (n=85) | Total (n=158) | P value | |||
---|---|---|---|---|---|---|---|
No. | Percent | No. | Percent | No. | Percent | ||
HIN | 61 | 83.6% | 26 | 30.6% | 87 | 55.1% | 0.001* |
DM | 59 | 80.8% | 16 | 18.8% | 75 | 47.5% | 0.001* |
WC Total Male Female |
41 18 23 |
56.2% 24.7% 31.5% |
24 12 12 |
28.2% 14.1% 14.1% |
65 30 35 |
35.1% 18.9% 22.2% |
0.053 |
Triglyceride | 51 | 69.9% | 21 | 24.7% | 72 | 45.6% | 0.001* |
HDL | 61 | 83.6% | 28 | 32.9% | 89 | 56.3% | 0.001* |
Table 2: Frequency of metabolic syndrome components in both groups.
Variables | Group A (M ± SD) |
Group B (M ± SD) |
Total (M ± SD) | P value |
---|---|---|---|---|
Cholesterol | 193.36 ± 48.93 | 182.67 ± 42.13 | 187.6 ± 45.57 | 0.142 |
Triglyceride | 179.15 ± 83.26 | 121.75 ± 43.19 | 148.27 ± 70.72 | 0.001* |
LDL | 96.86 ± 49.7 | 92.73 ± 42.14 | 94.64 ± 43.7 | 0.555 |
HDL | 34.12 ± 11.28 | 49.73 ± 16.35 | 42.52 ± 16. 2 | 0.001* |
Uric acid | 5.7 ± 1.56 | 6.57 ± 2.35 | 6.17 ± 2 | 0.008* |
Table 3: Laboratory results in both groups.
After results of psychometric tests, 100 patients (63.3%) have MCI, 55 patients of them had metabolic syndrome and remaining 58 patients (36.7%) had normal cognition (Table 4). The correlation of result of MMSE score with age of patients, sex, education level and smoking were insignificant (Tables 5 and 6). Also there is a significant correlation between MMSE score and all components of metabolic syndrome and with number of components of Metabolic syndrome, the increase in number of Metabolic syndrome components associated with low score of MMSE (Tables 7 and 8).
Variables | Group A (n=73) | Group B (n=85) | Total (n=158) |
|||
---|---|---|---|---|---|---|
No. | Percent | No. | Percent | No. | Percent | |
Normal cognitive | 18 | 24.66% | 40 | 47% | 58 | 36.7% |
MCI | 55 | 75.34% | 45 | 53% | 100 | 63.3% |
Table 4: Frequency of MCI among the studied patients.
Variables | MMS (M ± SD) | P value |
---|---|---|
Sex Male Female |
26.55 ± 1.97 26.29 ± 1.9 |
0.434 |
Education level Illiterate Read and write Educated |
26.39 ± 2.17 26.46 ± 1.77 26.58 ± 1.95 |
0.896 |
Smoking Positive Negative |
27.21 ± 1.63 26.58 ± 1.92 |
0.113 |
Table 5: Correlation between result of MMSE score and demographic data.
Variables | (M ± SD) | MMS (M ± SD) | P value |
---|---|---|---|
Age | 70.8 ± 5.64 | 26.46 ± 1.95 | 0.295 |
BMI | 27.27 ± 4.22 | 26.46 ± 1.95 | 0.032* |
WC | 91.69 ± 14.4 | 26.46 ± 1.95 | 0.04* |
Table 6: Correlation between result of MMSE score and age, BMI and WC.
Variable | MMS (M ± SD) | P value |
---|---|---|
WC Normal High |
25.77± 1.64 26.95 ± 2.00 |
0.001* |
Hypertension Positive Negative |
26.03± 2.04 26.99 ± 1.69 |
0.002* |
Diabetes mellitus Positive Negative |
25.61± 1.94 27.23 ± 1.62 |
0.001* |
Triglyceride Normal High |
26.04± 1.92 26.81 ± 1.91 |
0.013* |
HDL Normal Low |
25.98± 1.83 27.09 ± 1.95 |
0.001* |
Table 7: Correlation between result of MMSE score and result of laboratories.
Number | MMSE score (M ± SD) | P value |
---|---|---|
0 component | 28.63± 1.21 | 0.0001* |
One component | 27.68± 1.47 | |
Two components | 26.33± 1.67 | |
Three components | 26.41± 2.18 | |
Four components | 25.54± 1.72 | |
Five components | 24.53± 0.92 |
Table 8: Correlation between result of MMSE score and number metabolic syndrome components.
Discussion
MCI is an important public health concern due to the increased risk of progression to dementia and increased mortality [20]. The concept of MCI permits timely identification of patients at high risk of developing dementia, thus opening a potentially larger therapeutic window and increasing the significance of modifiable risk factors [21,22]. Early diagnosis and intervention of MCI could postpone or prevent the onset of subsequent dementia. It is critical to identify potentially protective factors for the development of MCI and progression to dementia. One hundred and fifty eight patients aged 65 years old or more of both sex were included in the study, 73 patients (46.2%) have metabolic syndrome (group A) and 85 patients (53.8%) didn’t have metabolic syndrome (group B) with no significant difference between both groups regarding age, sex, education level. In our study we found that, metabolic syndrome prevalence was 46% among general populations (56%in females and 42% in males), National Health and Nutrition Survey [23] found the prevalence of metabolic syndrome among general populations to be 62.0%, 63.4% in female and 34.1% in male. Also, Oh et al. [24] reported the prevalence of metabolic syndrome was 63.8% in women and 31.4% in men. In the current study, the prevalence of MCI among studied patients was 63.3% which was higher than the prevalence of MCI reported in general population aged ≥ 65 years by several studies 12-18% [25,26], 14-40% [27,28] 10-25% [1] and 16-20% [21]. This difference can be explained as our study was hospital based study. The prevalence of MCI was higher among patients with metabolic syndrome (75.34%) than patients without metabolic syndrome (53%) with statistical significance. The score of MMSE was 25.74 ± 1.95 in patients with metabolic syndrome in comparison to 27.08 ± 1.73 in patients without metabolic syndrome. These results were agreed with Deme et al. [29] who reported that; metabolic syndrome correlates to lower MMSE scores and thus mild cognitive decline. The MMSE mean score of metabolic syndrome group is lower with -2.345 points compared to non-metabolic syndrome subjects. Graham et al. [25] and Yaffe et al. [30] reported that cognitive function decreased in the metabolic syndrome group compared to the normal control group. Also several cross-sectional studies reported that, metabolic syndrome was associated with significantly poorer cognitive performance [31-35]. In our study, the metabolic risk factors, diabetes mellitus, hypertension, WC, high triglyceride and low HDL levels affected the MMSE total score and significantly associated with MCI that were agreed with several studies reported that hypertension [36-38], diabetes mellitus [39], obesity [14,40], high triglyceride [41,42] and low HDL [43-47] have each been associated with cognitive impairment, ranging from MCI to dementia. The score of MMS was inversely related with number of Metabolic syndrome components, increase in number of metabolic syndrome components associated with increasing degree of cognitive impairment, that agree with [48] who report the same results. In the Longitudinal Aging Study Amsterdam [35], hyperglycemia was a key predictor, while HDL-C was found to be the most important predictor in the current study as noted above, and this was agree with [49], while [50] concluded that, high triglycerides was the most important predictor of vascular dementia. Regarding DM and cognitive impairment, we found a significant positive correlation; these results were agreed with Brownlee [51], Farris et al. [52], Den Heijer et al. [53], Biessels et al. [54], Sonnen et al. [55] and Balakrishnan et al. [56], they found same results. Also in our study we found a positive correlation between HTN and impaired cognition, this result was agree with Gorelick et al. [57], Okusaga et al. [58], Uiterwijk et al. [59], Spinelli et al. [60], Yamaguchi et al. [61] and Kilander et al. [62], they reported same correlation, our result was disagreed with Gifford et al. [63] who found an inverse relationship between blood pressure and cognitive dysfunction. Hypertension is said to decrease the number of nicotinic receptors sensitive to acetylcholine and to cause cerebrovascular diseases, cerebral infarction and cerebral gray substances, arteriosclerosis and lower cognitive function [64]. The combination of type II diabetes and hypertension is associated with greater cognitive impairment compared to normotensive diabetic patients [65]. Large population-based studies then revealed that hyperlipidemia and particularly hypercholesterolemia in middle age are associated with the risk of subsequent occurrence of MCI [66-68]. Hypertriglyceridemia changes cerebral blood by increasing the viscosity of blood and lowers cognitive function by causing arteriosclerosis [69] Lower HDL-C level is associated with more severe lesions of white matter changes, leading to MCI, even AD [70]. HDL-C has been described as a negative risk factor for the development of cognitive impairment [71]. HDL-C can prevent aggregation and polymerization of β-amyloid, thus slowing or even preventing the development of AD [72,73]. HDL-C is also has anti-inflammatory properties [74]. Abdominal obesity was associated with cognitive dysfunction as defined by scores obtained on a MMSE developed for the assessment of cognitive functioning in individuals over 65 years, even after adjustment for age [75]. Adiposity has a direct effect on neuronal degradation [76]. Obesity is also associated with subclinical inflammatory status, a condition linked to dementia [77] and cognitive decline [78]. Although the association between obesity and poor cognitive function is prominent in the elderly, middle-aged, obese adults may have a greater degree of brain atrophy compared with age-matched, non-obese people [9]. Non-elderly obese people may experience subtle cognitive dysfunction and may be at greater risk of progression to significant cognitive impairment [79].
Conclusion
Patients with metabolic syndrome have a higher risk for developing cognitive impairment and this risk increase with increased number of metabolic syndrome components.
References
- Förstl H, Bickel H, Frölich L (2009) MCI-plus: Leichte cognitive Beeinträchtigung mit rascher Progredienz. Teil I: Prävention und Therapie. Dtsch Med Wochenschr 134: 39-44.
- The Ministry of Health and Welfare (2006) The third Korea national health and nutrition examination survey (KNHANES III).
- Deme SM, Nanu PD, Jianu CD, Kory-Calomfirescu S, Ioncu DS (2010) The correlation between cognitive decline and the incidence and the influence of metabolic syndrome in elderly subjects with mild cognitive decline. Journal Medical Aradean (Arad Medical Journal) 13: 11-18.
- Waldstein SR, Katzel LI (2001) Hypertension and cognitive function. In: Wldstein I SR, Elias MF, editors. Neuropsychology of cardiovascular disease. Mahwah, NJ: Lawrence Erlbaum Associates, pp: 5-36.
- McCrimmon RJ, Ryan CM, Frier BM (2012) Diabetes and cognitive dysfunction. Lancet 379: 2291-2299.
- De Frias CM, Bunce D, Wahlin A, Adolfsson R, Sleegers K, et al. (2007) Cholesterol and triglycerides moderate the effect of apolipoprotein E on memory functioning in older adults. J Gerontol B Psychol Sci Soc Sci 62: 112-118.
- Atzmon G, Gabriely I, Greiner W, Davidson D, Schechter C, et al. (2002) Plasma HDL levels highly correlate with cognitive function in exceptional longevity. J Gerontol A Biol Sci Med Sci 57: 712-715.
- Balakrishnan S, Mathew J, Antony S, Paulose CS (2009) Muscarinic M(1), M(3) receptors function in the brainstem of streptozotocin induced diabetic rats: Their role in insulin secretion from the pancreatic islets as a function of age. Eur J Pharmacol 608: 14-22.
- Gorelick PB, Scuteri A, Black SE, Decarli C, Greenberg SM, et al. (2011) Vascular contributions to cognitive impairment and dementia: A statement for healthcare professionals from the American Heart Association/American Stroke Association. Stroke 42: 2672-2713.
- Okusaga O, Stewart MC, Butcher I, Deary I, Fowkes FG, et al. (2013) Smoking, hypercholesterolaemia and hypertension as risk factors for cognitive impairment in older adults. Age Ageing 42: 306-311.
- Uiterwijk R, Huijts M, Staals J, Duits A, Gronenschild E, et al. (2014) Subjective cognitive failures in patients with hypertension are related to cognitive performance and cerebral micro bleeds. Hypertension 64: 653-657.
- Spinelli C, De Caro MF, Schirosi G, Mezzapesa D, De Benedittis L, et al. (2014) Impaired cognitive executive dysfunction in adult treated hypertensive with a confirmed diagnosis of poorly controlled blood pressure. Int J Med Sci 11: 771-778.
- Yamaguchi Y, Wada M, Sato H, Nagasawa H, Koyama S, et al. (2015) Impact of nocturnal heart rate variability on cerebral small-vessel disease progression: A longitudinal study in community-dwelling elderly Japanese. Hypertens Res 38: 564-569.
- Kilander L, Nyman H, Boberg M, Hansson L, Lithell H (1998) Hypertension is related to cognitive impairment: A 20 year follow-up of 999 men. Hypertension 31: 780-786.
- Geerlings MI, Appelman AP, Vincken KL, Algra A, Witkamp TD, et al. (2010) Brain volumes and cerebrovascular lesions on MRI in patients with atherosclerotic disease. The SMART-MR study. Atherosclerosis 210: 130-136.
- Petrova M, Prokopenko S, Pronina E, Mozheyko E (2010) Diabetes type 2, hypertension and cognitive dysfunction in middle age women. J Neurol Sci 299: 39-41.
- Kivipelto M, Helkala EL, Hänninen T, Laakso MP, Hallikainen M, et al. (2001) Midlife vascular risk factors and late-life mild cognitive impairment: A population-based study. Neurology 56: 1683-1689.
- Dufouil C, Richard F, Fiévet N, Dartigues JF, Ritchie K, et al. (2005) APOE genotype, cholesterol level, lipid-lowering treatment, and dementia: The three-city study. Neurology 64: 1531-1538.
- Whitmer RA, Karter AJ, Yaffe K, Quesenberry CP Jr, Selby JV (2009) Hypoglycemic episodes and risk of dementia in older patients with type 2 diabetes mellitus. JAMA 301: 1565-1572.
- Koenig W, Sund M, Ernst E, Mraz W, Hombach V, et al. (1992) Association between rheology and components of lipoproteins in human blood. Results from the MONICA project. Circulation 85: 2197-2204.
- Zhuang L, Sachdev PS, Trollor JN, Kochan NA, Reppermund S, et al. (2012) Microstructural white matter changes in cognitively normal individuals at risk of amnestic MCI. Neurology 79: 748-754.
- Castano EM, Prelli F, Wisniewski T, Golabek A, Kumar RA, et al. (1995) Fibrillogenesis in Alzheimer's disease of amyloid beta peptides and apolipoprotein E. Biochem J 306 : 599-604.
- Cockerill GW, Rye KA, Gamble JR, Vadas MA, Barter PJ (1995) High density lipoproteins inhibit cytokine-induced expression of endothelial cell adhesion molecules. Arterioscler Thromb Vasc Biol 15: 1987-1994
- McGeer EG, McGeer PL (1998) The importance of inflammatory mechanisms in Alzheimer disease. Exp Gerontol 33: 371-378.
- Cockerill GW, Huehns TW, Weerasinghe A, Stocker C, Lerch PG, et al. (2001) Elevation of plasma high-density lipoprotein concentration reduces interleukin-1-induced expression of E-selection in an in vivo model of acute inflammation. Circulation 103: 108-112.
- Jeong SK, Nam HS, Son MH, Son EJ, Cho KH (2005) Interactive effect of obesity indexes on cognition. Dement Geriatr Cogn Disord 19: 91-96.
- Whitmer RA, Gunderson EP, Barrett-Connor E, Quesenberry CP Jr, Yaffe K (2005) Obesity in middle age and future risk of dementia: A 27 year longitudinal population based study. BMJ 330: 1360.
- Schmidt RE, Dorsey DA, Beaudet LN, Parvin CA, Zhang W, et al. (2004) Experimental rat models of types 1 and 2 diabetes differ in sympathetic neuroaxonal dystrophy. J Neuropathol Exp Neurol 63: 450-460.
- Teunissen CE, van Boxtel MP, Bosma H, Bosmans E, Delanghe J, et al. (2003) Inflammation markers in relation to cognition in a healthy aging population. J Neuroimmunol 134: 142-150.
- Ward MA, Carlsson CM, Trivedi MA, Sager MA, Johnson SC (2005) The effect of body mass index on global brain Volume in middle-aged adults: A cross sectional study. BMC Neurol 5: 23.
Citation: Hashem HA, Mustafa YH (2018) Correlation between Metabolic Syndrome and Mild Cognitive Impairment. J Alzheimers Dis Parkinsonism 8: 414. DOI:
Copyright: ©2018 Hashem HA, et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Share This Article
Recommended Journals
ºÚÁÏÍø Journals
Article Tools
Article Usage
- Total views: 5093
- [From(publication date): 0-2018 - Mar 10, 2025]
- Breakdown by view type
- HTML page views: 4324
- PDF downloads: 769