Type 2 Diabetes Mellitus and Cognitive Function in the Elderly

authors:

avatar Nazila Malekian 1 , avatar Seyed Reza Hosseini ORCID 2 , avatar Sussan Moudi ORCID 2 , * , avatar Mohammad Ali Bayani 3 , avatar Farzan Kheirkhah ORCID 2 , avatar Ali Bijani ORCID 2 , avatar Aylar Khalilipour ORCID 1

Faculty of Medicine, Babol University of Medical Sciences, Babol, IR Iran
Social Determinants of Health Research Center, Health Research Institute, Babol University of Medical Sciences, Babol, IR Iran
Department of Internal Medicine, Babol University of Medical Sciences, Babol, IR Iran
Iranian Journal of Psychiatry and Behavioral Sciences: Vol.12, issue 2; e9494
published online: May 30, 2018
article type: Original Article
received: April 25, 2017
revised: August 7, 2017
accepted: August 21, 2017
DOI: https://doi.org/10.5812/ijpbs.9494

how to cite: Malekian N, Hosseini S R, Moudi S, Bayani M A, Kheirkhah F, et al. Type 2 Diabetes Mellitus and Cognitive Function in the Elderly. Iran J Psychiatry Behav Sci. 2018;12(2):e9494. https://doi.org/10.5812/ijpbs.9494.

Abstract

Background:

Cognitive impairment is one of the complications experienced by older adults with diabetes.

Objectives:

This study was conducted to assess the association of cognitive function with the glycemic condition of the elderly population.

Methods:

This analytic cross-sectional study was conducted on individuals 60 years and over in Babol, Northern Iran, during 2014 and 2015. Sociodemographic characteristics, history of other chronic diseases, medications, physical examination, fasting blood glucose, and serum lipid profile were used for data collection. MMSE was used to assess cognitive function and GDS for depressive symptoms.

Results:

A total of 1,503 individuals participated in the study. The mean age of the participants was 69.07 ± 7.28 years; of them, 1,038 (69.1%) were normoglycemic (non-diabetic) and 465 had (31.9%) diabetes mellitus. There were significant differences in weight, BMI, systolic blood pressure, serum TG, LDL, and past medical history of MI or angina pectoris between diabetic and non-diabetic patients (P < 0.05). Of the elderly, 1,042 (69.3%) had normal cognition and 461 (30.7%) showed impaired cognition according to MMSE cut values. The mean of MMSE score in non-diabetic and diabetic patients was 25.51 ± 3.40 (25.30 - 25.72) and 25.02 ± 3.86 (24.63 - 25.46), respectively (P = 0.018). A significant difference was observed in the severity of cognitive impairment between the two groups (P = 0.048).

Conclusions:

Older adults with diabetes mellitus have poorer cognitive functions, therefore, health care providers and family physicians should pay more attention to the identification of any cognitive decline in the initial stages of diabetes mellitus.

1. Background

Type 2 diabetes mellitus (DM) is increasing worldwide, and the disease, as a significant public health problem, has been found in 22.0% of individuals aged 60 years and over in Iran (1). Diabetic patients are at high risk for vascular damages leading to nephropathy, retinopathy, neuropathy, and cardiovascular and cerebrovascular diseases. Previous studies suggest that cognitive impairment is another complication that the elderly with diabetes may encounter (2-9). However, the American diabetes association (ADA) has not included cognitive disorder in its 2015 treatment guidelines as an important complication of type 2 diabetes (10).

Although risk factors associated with the harmful effects of type 2 diabetes on accelerated cognitive aging need to be more researched, cerebral microvascular damages might have a significant part to play (11-13). Some risk factors for dementia and cognitive decline in patients with diabetes are duration of disease, hyperglycemia, insulin therapy, and peripheral arterial disease (14-17). Cognitive dysfunction in type 2 diabetic patients may be due to the interaction of metabolic abnormalities related to diabetes (hyperglycemia and hyperinsulinemia), diabetes-specific complications (retinopathy, nephropathy, and neuropathy), and other diabetes-related disorders (ischemic heart disease, cerebrovascular disease, hypertension, low serum HDL cholesterol, central obesity, and depression) (18, 19). In addition, other processes such as advanced glycation end product accumulation or changes in cerebral insulin signaling may promote Alzheimer’s disease (20, 21).

Impairment in cognitive functions, such as planning, organizing, insight and attention, is found in patients with diabetes (22-26). Considering the importance of self-management behaviors in the treatment of diabetes and the high complexity of treatment regimens (eg, blood glucose testing, meal planning, and prevention of acute conditions associated with diabetes treatment such as hypoglycemia and treatment compliance), diabetic patients with cognitive dysfunction may experience significant difficulty in managing their already complicated disease.

Furthermore, identifying diabetes as a modifiable risk factor can help delay the occurrence of dementia (5). Early detection and proper intervention for dementia is consistent with high-quality health care goals and can significantly improve the well- being of both those with dementia and family members who are involved in providing care (27).

2. Objectives

This study aimed at examining the association between specific measures of cognitive function and the glycemic condition of the elderly who participated in the longitudinal study of Amirkola health and ageing project (AHAP) in Babol, Iran (28).

3. Materials and Methods

This analytical cross-sectional study was conducted on elderly participants of AHAP study (28) in Amirkola, Babol, Northern Iran, during 2014 and 2015. In AHAP study (28), all 2234 individuals aged 60 years and over who were living in Amirkola were invited to participate in the study. Of them, 1616 elders participated in the study (response rate: 72.3%). All 1616 senior citizens who were present in the two health centers of Amirkola were invited to participate in the stud by phone or home visits. Data on sociodemographic characteristics, history of other chronic diseases (eg, myocardial infarction or angina pectoris), and diabetes- specific measures, such as medications, were collected using a questionnaire. Each assessment round consisted of a physical examination including height, weight, and blood pressure measurements, which was performed by the educated staff at the research center. Body mass index (BMI) was calculated as weight (in kilograms) divided by the square of height (in meters). Blood pressure was measured with the participant in the supine position using a calibrated sphygmomanometer (29). Total and HDL cholesterol were measured using standardized enzymatic methods. The history of myocardial infarction or angina pectoris was defined as a self-reported physician’s diagnosis.

Fasting early morning venous blood samples were collected to assess fasting blood sugar (FBS), total cholesterol, high density lipoprotein (HDL) cholesterol, low density lipoprotein (LDL) cholesterol, and triglycerides (TG) levels. Patients with diabetes were defined based on a self-report confirmed by the general practitioner, self-report alone when no general practitioner verification was available, and by diabetic medication (hypoglycemic medications and/or insulin); however, no self-report of diabetes, no use of diabetes medication, and two fasting blood glucose levels more than or equal to 126 mg/dL were also considered (30, 31).To consider other factors that might have moderated the association between diabetes and cognitive function, we examined the effects of other drugs that were assessed from the pharmaceutical blisters or vials of the participants.

Mini-mental state examination (MMSE) was used to assess cognitive function. This test is a commonly used and reliable scale for assessing the cognitive level of an individual (32). This test is quick to administer at bedside (33-35) and assesses several aspects of cognition using specific questions related to attention, orientation, memory, calculation, and language. Those patients whose score was less than 25/30 are considered to be having cognitive impairment (34). MMSE includes specific questions, and scoring is based on 30 total points, with the scores of 25 to 30 as cognitive impairment, 20 to 25 as mild, 10 to 20 as moderate, and 0 to 10 as severe cognitive impairment. The reliability and validity of the Persian version of this test was examined, showing a valid and reliable measure for screening cognitive impairment in elderly Iranians, and it has overall sensitivity and specificity of 98% and 100%, respectively (36).

The 15-item geriatric depression scale (GDS) was used to assess depressive symptoms. It is a well-validated tool often used to screen depressive symptoms in older individuals (37). This measure is scored based on a 15-point scale and impairment is indicated by a score of 6 or higher (37-39). Its reliability and validity have been assessed in elderly Iranians and it proved to be a proper screening instrument for major depression evaluation in the elderly in Iran (38).

Patients with severe visual impairment, who were unable to complete the tests, were excluded from the study.

For statistical analysis, demographic and health- related characteristics were compared between the two diabetic and non-diabetic groups. T test, chi-square, ANOVA, and logistic regression tests were used for data analysis. All analyses were performed using SPSS software (Version 16).

This research was approved by the ethics committee of Babol University of Medical Sciences (ethical committee approval code: MUBABOL.REC.1392.4).

4. Results

Out of 1616 elderly individuals (≥ 60 years old), 1,503 were enrolled in our study; of them, 835 were male (55.6%) and 668 female (44.4%). The mean age of the participants was 69.07 ± 7.28 (minimum 60 and maximum age 92) years. Of them, 95 (6.3%) were unemployed, 589 (39.2%) housekeepers, 478 (31.8%) employed - except housekeeping-, 331 (22.0%) retired, and occupation was not mentioned in 8 cases.

Of the participants, 465 (31.9%) had diabetes and 1038 (69.1%) were normoglycemic (non-diabetic). Their general baseline characteristics are demonstrated in Tables 1 and 2. There were significant differences in weight, BMI, systolic blood pressure, serum TG, LDL, and past medical history of MI or angina pectoris between diabetic and non-diabetic patients (P value < 0.05).

Table 1.

General Baseline Characteristics (Quantitative Variables) of the Study Participants

VariableMean ± Standard Deviation ValuesP Value
With DiabetesWithout Diabetes
Age, y68.33 ± 6.94169.40 ± 7.4090.008
Height, m157.340 ± 8.81157.500 ± 9.410.755
Weight, kg69.565 ± 12.7366.744 ± 12.87< 0.001
BMI, kg/m228.07 ± 4.5126.78 ± 4.51< 0.001
Systolic blood pressure, mmHg145.79 ± 22.99141.32 ± 21.62< 0.001
Diastolic blood pressure, mmHg82.17 ± 12.2281.15 ± 11.660.122
Fasting blood sugar, mg/dL163.70 ± 59.6898.20 ± 11.24< 0.001
Serum total cholesterol196.03 ± 46.57197.47 ± 39.570.564
TG, mg/dL182.69 ± 96.35150.60 ± 76.52< 0.001
HDL, mg/dL38.83 ± 4.6638.68 ± 4.250.535
LDL, mg/dL122.32 ± 39.91128.65 ± 34.550.004
MMSE score25.02 ± 3.8625.51 ± 3.400.018
Table 2.

General Baseline Characteristics (Qualitative Variables) of the Study Participants

Variable/GroupsNo. (%)P Value
With DiabetesWithout Diabetes
Gender< 0.001
Male47.559.2
Female52.540.8
Age0.168
60 - 6439.135.8
65 - 6923.219.8
70 - 7415.518.6
75 - 7914.815.4
80 - 845.26.8
≥ 852.23.5
Marital status0.134
Married82.486.9
Widow11.89.2
Widower5.60.2
Divorced5.63.8
Educational level0.34
Illiterate65.662.7
Primary and secondary school26.930.5
High school and University7.56.7
Occupation< 0.001
Unemployed8.85.2
Housekeeper45.836.4
Retired20.222.8
Occupying (except housekeeping)24.735
Unknown0.40.6
Glucose lowering drugs< 0.001
Yes54.80.4
No45.299.6
Past history of Myocardial Infarction< 0.001
Yes93.9
Past history of angina pectoris0.003
Yes22.215.6
Depressed (according to GDS)< 0.001
Yes50.938.7
MMSE score < 250.029
Yes34.628.9
Body mass index, kg/m2< 0.001
< 25 21.937.7
25 - 29.9948.840.3
≥ 3029.222

Of the elderly, 1,042 (69.3%) had normal cognition and 461 (30.7%) showed impaired cognition according to MMSE cut values. Mean, SD, and 95% confidence interval for the mean of MMSE score in the two groups were calculated as 25.51 ± 3.40 (25.30 - 25.72) and 25.02 ± 3.86 (24.63 - 25.46), respectively (P = 0.018).

The association of cognitive condition with diabetes status is presented in Table 3. Also, we compared the prevalence of cognitive impairment (MMSE score less than 25/30) in the two groups and the results revealed that the prevalence of cognitive impairment was higher in the diabetic group (OR: 1.303, 95% CI: 1.032 - 1.645, P = 0.029).

Table 3.

The Association of Cognitive Condition with the Diabetes Statusa

Diabetes StatusNormal MMSEMild Impaired CognitionModerate Impaired CognitionSevere Impaired CognitionTotalP Value
Without diabetes738 (71.1)233 (22.4)65 (6.3)2 (0.2)1038 (100)0.048
With diabetes304 (65.4)121 (26.0)36 (7.7)4 (0.9)465 (100)

aValues are expressed as No. (%).

All the associated variables that had been assessed (gender, age, educational level, occupational status, BMI, antidiabetic medication, past history of myocardial infarction, past history of angina pectoris, and depression-according to GDS-) were entered into logistic regression analysis. The adjusted odds ratio of cognitive impairment is demonstrated in Table 4.

Table 4.

Adjusted Odds Ratio of Cognitive Impairment According to Gender, Age, Educational Level, Occupational Status, BMI, Antidiabetic Medication, Depression and Past History of Cardiovascular Disorders

VariableAdjusted OR for Cognitive Impairment (95% CI)P Value
With diabetes1.359 (0.950 - 1.944)0.093
Females3.013 (2.128 - 4.267)< 0.001
Age, y
60 - 641< 0.001
65 - 691.267 (0.875 - 1.833)0.050
70 - 741.461 (1.000 - 2.134)0.051
75 - 793.444 (2.330 - 5.090)< 0.001
80 - 844.401 (2.590 - 7.479)< 0.001
≥ 855.691 (2.796 - 11.581)< 0.001
Educational level
Illiterate5.598 (4.037 - 7.763)< 0.001
Occupation
Unemployed1.626 (1.122 - 2.357)0.010
Body mass index, kg/m2
< 2510.006
25 - 29.990.608 (0.448 - 0.825)0.001
> 300.754 (0.528 - 1.075)0.118
Antidiabetic medication use0.792 (0.510 - 1.230)0.299
Past history of myocardial infarction0.942 (0.526 - 1.686)0.841
Past history of angina pectoris0.777 (0.554 - 1.092)0.146
Depressed (according to GDS)1.359 (0.950 - 1.944)0.093

The level of fasting blood glucose had a significant association with MMSE scores, interestingly with differences between the two sexes. When FBS level increased, MMSE score decreased in females, while the MMSE score adversely increased in males (Figure 1). We examined the interaction between gender and diabetes mellitus using two-way ANOVA; no significant interaction was found between sex and diabetes (P = 0.187).

Gender, FBS and MMSE score
Gender, FBS and MMSE score
Figure 1.

Gender, FBS and MMSE score

5. Discussion

Our findings revealed that older adults with diabetes mellitus have poorer cognitive functions, and there is a 1.3- fold increased risk of cognitive impairment among people with diabetes. This finding was similar to the research of Van den Berg in which the association of four vascular risk factors (type 2 diabetes, obesity, dyslipidemia, and hypertension) with impaired cognitive functioning was reviewed. They suggested that all the four mentioned risk factors could cause a decline in cognitive functioning, but the association was most consistent in type 2 diabetes and hypertension (40). Furthermore, the statement of Waterloo University declared that type 2 diabetes was associated with poor performance on cognitive tests measuring (41). The study of Logroscino that examined the association of type 2 diabetes with baseline cognitive function and cognitive decline over two years of follow- up in women aged 70 to 81 years, it was found that women with type 2 diabetes had increased odds of poor cognitive function (25% - 35% increased odds of poor baseline score) and substantial cognitive decline (5). The findings of Yaffe study are also compatible with our findings, as they indicated that diabetes mellitus and poor glucose control among diabetic patients are associated with poor cognitive function and greater later decline (6). This higher cognitive impairment in diabetic patients might be correlated to different consequences of diabetes, such as patient’s glycemic condition and micro- and macrovascular damages (19). Body mass index (P value < 0.001), systolic blood pressure (P < 0.001), serum triglyceride level (P < 0.001), and past medical history of MI or angina pectoris (P < 0.05) were significantly higher in diabetic patients than non- diabetic patients.

In our study, higher fasting blood glucose levels were associated with an increased risk of impaired cognition, which is consistent with the results of Crane et al. (42) and Yaffe et al. (6) studies in which they suggested that the severity of diabetes may contribute to accelerated cognitive aging. A wide range of cognitive domains can be impaired in older patients with type 2 diabetes. In the study of Zhou et al. (43), it was mentioned that insulin and its signaling pathway not only regulates glucose metabolism, but also modulates learning and memory. Moreover, in elderly patients with diabetes, it was reported that there is a reduction in cerebral perfusion of the frontotemporal region that plays an important role in memory, judgment, attention, learning ability, and other functions. The study of Ramos-Rodriguez et al. (44) revealed that central vascular disease is related to exacerbated pathology in patients with type 2 diabetes and Alzheimer’s disease.

Older patients with diabetes and concomitant cognitive dysfunction may not be able to follow treatment regimens, such as multiple oral medications, several daily insulin injections, and dietary regimen. These patients can be at increased risk of treatment complications, such as omission of meals leading to hypoglycemia or incorrect dose of drugs. The fact that 17.6% of our study patients who had diabetes did not have a partner is a matter of concern because they may be living alone and the complications associated with their impaired cognitive function can be even more complex.

In our study, patients with diabetes reported depressive symptoms (according to GDS) more than non-diabetic patients (P < 0.001). In a previous study conducted in a similar study population, it was mentioned that the mean of MMSE score was higher in non-depressed elderly (26.0 ± 3.2) compared to depressed ones (24.1 ± 4.5), P < 0.001 (34). Depression in patients with diabetes can increase the health care needs and finances (26); also, self-management of diabetes can be affected by depression (19).

In this study, the level of blood glucose had a significant association with MMSE scores, but this result manifested differently among the two genders: when FBS increased, MMSE scores decreased in females, but the scores increased in males. There was no significant statistical interaction between sex and diabetes mellitus, and this result may be due to the impact of sexual hormones. However, it is highly recommended to conduct studies to investigate the effects of sexual hormones on cognitive function of older adults. In his research, Logroscino has mentioned that type 2 DM affected older women and men disproportionately and suggested further studies to investigate the impact of diabetes on cognition in older women (5). Beauchet indicated that low serum levels of testosterone may be related to cognitive decline in healthy older men (45). Hogervorst reviewed the effects of increasing testosterone on cognitive functions in elderly men and women and concluded that low testosterone levels may predispose to Alzheimer’s disease in men (46). Moreover, Janicki suggested that changes in estrogen levels during ageing may increase the risk of cognitive impairment (47).

The strengths of our study were its community-based sample, its large number of elderly diabetic subjects, and the physical examination and laboratory tests performed to assess the measures that were potentially associated with diabetes and/or cognitive functions.

We evaluated cognitive dysfunctions using MMSE that has been reported to have low sensitivity in detecting subtle cognitive impairment, and this was a limitation of this study. Short physical examination and assessment tools, such as MMSE, have limitations in detecting subtle cognition changes (26). We suggest more sensitive tools to identify subtle cognitive impairments for further studies.

To provide care for the elderly, health care providers and family physicians should pay sufficient attention to identify any cognitive decline in its initial stages in the elderly with impaired fasting blood sugar and determine the association between blood glucose level and cognitive function.

Acknowledgements

References

  • 1.

    Taheri Tanjani P, Moradinazar M, Esmail Mottlagh M, Najafi F. The prevalence of diabetes mellitus (DM) type II among Iranian elderly population and its association with other age-related diseases, 2012. Arch Gerontol Geriatr. 2015;60(3):373-9. [PubMed ID: 25623857]. https://doi.org/10.1016/j.archger.2014.11.012.

  • 2.

    Koekkoek PS, Kappelle LJ, van den Berg E, Rutten GE, Biessels GJ. Cognitive function in patients with diabetes mellitus: guidance for daily care. Lancet Neurol. 2015;14(3):329-40. [PubMed ID: 25728442]. https://doi.org/10.1016/S1474-4422(14)70249-2.

  • 3.

    Arvanitakis Z, Wilson RS, Li Y, Aggarwal NT, Bennett DA. Diabetes and function in different cognitive systems in older individuals without dementia. Diabetes Care. 2006;29(3):560-5. [PubMed ID: 16505506].

  • 4.

    Luchsinger JA, Reitz C, Patel B, Tang MX, Manly JJ, Mayeux R. Relation of diabetes to mild cognitive impairment. Arch Neurol. 2007;64(4):570-5. [PubMed ID: 17420320]. https://doi.org/10.1001/archneur.64.4.570.

  • 5.

    Logroscino G, Kang JH, Grodstein F. Prospective study of type 2 diabetes and cognitive decline in women aged 70-81 years. BMJ. 2004;328(7439):548. [PubMed ID: 14980984]. [PubMed Central ID: PMC381043]. https://doi.org/10.1136/bmj.37977.495729.EE.

  • 6.

    Yaffe K, Blackwell T, Kanaya AM, Davidowitz N, Barrett-Connor E, Krueger K. Diabetes, impaired fasting glucose, and development of cognitive impairment in older women. Neurology. 2004;63(4):658-63. [PubMed ID: 15326238].

  • 7.

    Duron E, Hanon O. Vascular risk factors, cognitive decline, and dementia. Vasc Health Risk Manag. 2008;4(2):363-81. [PubMed ID: 18561512]. [PubMed Central ID: PMC2496986].

  • 8.

    Pasquier F, Boulogne A, Leys D, Fontaine P. Diabetes mellitus and dementia. Diabetes Metab. 2006;32(5 Pt 1):403-14. [PubMed ID: 17110895].

  • 9.

    Biessels GJ, Staekenborg S, Brunner E, Brayne C, Scheltens P. Risk of dementia in diabetes mellitus: a systematic review. Lancet Neurol. 2006;5(1):64-74. [PubMed ID: 16361024]. https://doi.org/10.1016/S1474-4422(05)70284-2.

  • 10.

    American Diabetes Association. Standards of medical care in diabetes. Diabetes Care. 2015;38:S1-3.

  • 11.

    Starr JM, Wardlaw J, Ferguson K, MacLullich A, Deary IJ, Marshall I. Increased blood-brain barrier permeability in type II diabetes demonstrated by gadolinium magnetic resonance imaging. J Neurol Neurosurg Psychiatry. 2003;74(1):70-6. [PubMed ID: 12486269]. [PubMed Central ID: PMC1738177].

  • 12.

    Manschot SM, Brands AM, van der Grond J, Kessels RP, Algra A, Kappelle LJ, et al. Brain magnetic resonance imaging correlates of impaired cognition in patients with type 2 diabetes. Diabetes. 2006;55(4):1106-13. [PubMed ID: 16567535].

  • 13.

    van Harten B, Oosterman J, Muslimovic D, van Loon BJ, Scheltens P, Weinstein HC. Cognitive impairment and MRI correlates in the elderly patients with type 2 diabetes mellitus. Age Ageing. 2007;36(2):164-70. [PubMed ID: 17350976]. https://doi.org/10.1093/ageing/afl180.

  • 14.

    Peila R, Rodriguez BL, Launer LJ, Honolulu-Asia Aging S. Type 2 diabetes, APOE gene, and the risk for dementia and related pathologies: The Honolulu-Asia Aging Study. Diabetes. 2002;51(4):1256-62. [PubMed ID: 11916953].

  • 15.

    Ott A, Stolk RP, van Harskamp F, Pols HA, Hofman A, Breteler MM. Diabetes mellitus and the risk of dementia: The Rotterdam Study. Neurology. 1999;53(9):1937-42. [PubMed ID: 10599761].

  • 16.

    Gregg EW, Yaffe K, Cauley JA, Rolka DB, Blackwell TL, Narayan KM, et al. Is diabetes associated with cognitive impairment and cognitive decline among older women? Study of Osteoporotic Fractures Research Group. Arch Intern Med. 2000;160(2):174-80. [PubMed ID: 10647755].

  • 17.

    Bruce DG, Davis WA, Casey GP, Starkstein SE, Clarnette RM, Foster JK, et al. Predictors of cognitive impairment and dementia in older people with diabetes. Diabetologia. 2008;51(2):241-8. [PubMed ID: 18060658]. https://doi.org/10.1007/s00125-007-0894-7.

  • 18.

    Strachan MW, Deary IJ, Ewing FM, Frier BM. Is type II diabetes associated with an increased risk of cognitive dysfunction? A critical review of published studies. Diabetes Care. 1997;20(3):438-45. [PubMed ID: 9051402].

  • 19.

    McCrimmon RJ, Ryan CM, Frier BM. Diabetes and cognitive dysfunction. Lancet. 2012;379(9833):2291-9. [PubMed ID: 22683129]. https://doi.org/10.1016/S0140-6736(12)60360-2.

  • 20.

    Spauwen PJ, van Eupen MG, Kohler S, Stehouwer CD, Verhey FR, van der Kallen CJ, et al. Associations of advanced glycation end-products with cognitive functions in individuals with and without type 2 diabetes: the maastricht study. J Clin Endocrinol Metab. 2015;100(3):951-60. [PubMed ID: 25459912]. https://doi.org/10.1210/jc.2014-2754.

  • 21.

    Zhang P, Engelgau MM, Valdez R, Cadwell B, Benjamin SM, Narayan KM. Efficient cutoff points for three screening tests for detecting undiagnosed diabetes and pre-diabetes: an economic analysis. Diabetes Care. 2005;28(6):1321-5. [PubMed ID: 15920046].

  • 22.

    Gold AE, Deary IJ, Frier BM. Hypoglycemia and cognitive function. Diabetes Care. 1993;16(6):958-9. [PubMed ID: 8325222].

  • 23.

    Grande L, Milberg W, Rodolph J, Gaziano M, McGlinchey R. A timely screening for executive functions and memory. J Int Neuropsychol Soc. 2005;11(1):9-10.

  • 24.

    Kuo HK, Jones RN, Milberg WP, Tennstedt S, Talbot L, Morris JN, et al. Effect of blood pressure and diabetes mellitus on cognitive and physical functions in older adults: a longitudinal analysis of the advanced cognitive training for independent and vital elderly cohort. J Am Geriatr Soc. 2005;53(7):1154-61. [PubMed ID: 16108933]. [PubMed Central ID: PMC2763096]. https://doi.org/10.1111/j.1532-5415.2005.53368.x.

  • 25.

    Abbatecola AM, Paolisso G, Lamponi M, Bandinelli S, Lauretani F, Launer L, et al. Insulin resistance and executive dysfunction in older persons. J Am Geriatr Soc. 2004;52(10):1713-8. [PubMed ID: 15450050]. https://doi.org/10.1111/j.1532-5415.2004.52466.x.

  • 26.

    Munshi M, Grande L, Hayes M, Ayres D, Suhl E, Capelson R, et al. Cognitive dysfunction is associated with poor diabetes control in older adults. Diabetes Care. 2006;29(8):1794-9. [PubMed ID: 16873782]. [PubMed Central ID: PMC1615865]. https://doi.org/10.2337/dc06-0506.

  • 27.

    Bradford A, Kunik ME, Schulz P, Williams SP, Singh H. Missed and delayed diagnosis of dementia in primary care: prevalence and contributing factors. Alzheimer Dis Assoc Disord. 2009;23(4):306-14. [PubMed ID: 19568149]. [PubMed Central ID: PMC2787842]. https://doi.org/10.1097/WAD.0b013e3181a6bebc.

  • 28.

    Hosseini SR, Cumming RG, Kheirkhah F, Nooreddini H, Baiani M, Mikaniki E, et al. Cohort profile: the Amirkola Health and Ageing Project (AHAP). Int J Epidemiol. 2014;43(5):1393-400. [PubMed ID: 23918798]. https://doi.org/10.1093/ije/dyt089.

  • 29.

    Hosseini SR, Cumming RG, Sajjadi P, Bijani A. Chronic diseases among older people in Amirkola, northern Islamic Republic of Iran. East Mediterr Health J. 2011;17(11):843-9. [PubMed ID: 22276492].

  • 30.

    American Diabetes A. Diagnosis and classification of diabetes mellitus. Diabetes Care. 2010;33 Suppl 1:S62-9. [PubMed ID: 20042775]. [PubMed Central ID: PMC2797383]. https://doi.org/10.2337/dc10-S062.

  • 31.

    Jeon JY, Ko SH, Kwon HS, Kim NH, Kim JH, Kim CS, et al. Prevalence of Diabetes and Prediabetes according to Fasting Plasma Glucose and HbA1c. Diabetes Metab J. 2013;37(5):349-57. [PubMed ID: 24199164]. [PubMed Central ID: PMC3816136]. https://doi.org/10.4093/dmj.2013.37.5.349.

  • 32.

    Folstein MF, Folstein SE, McHugh PR. "Mini-mental state". A practical method for grading the cognitive state of patients for the clinician. J Psychiatr Res. 1975;12(3):189-98. [PubMed ID: 1202204].

  • 33.

    O'Bryant SE, Humphreys JD, Smith GE, Ivnik RJ, Graff-Radford NR, Petersen RC, et al. Detecting dementia with the mini-mental state examination in highly educated individuals. Arch Neurol. 2008;65(7):963-7. [PubMed ID: 18625866]. [PubMed Central ID: PMC2587038]. https://doi.org/10.1001/archneur.65.7.963.

  • 34.

    Kheirkhah F, Hosseini SR, Fallah R, Bijani A. [Prevalence of cognitive disorders in elderly people of Amirkola (2011-2012)]. Iran J Psychiatr Clin Psychol. 2014;19(4):247-54. Persian.

  • 35.

    Sheehan B. Assessment scales in dementia. Ther Adv Neurol Disord. 2012;5(6):349-58. [PubMed ID: 23139705]. [PubMed Central ID: PMC3487532]. https://doi.org/10.1177/1756285612455733.

  • 36.

    Ansari NN, Naghdi S, Hasson S, Valizadeh L, Jalaie S. Validation of a Mini-Mental State Examination (MMSE) for the Persian population: a pilot study. Appl Neuropsychol. 2010;17(3):190-5. [PubMed ID: 20799110]. https://doi.org/10.1080/09084282.2010.499773.

  • 37.

    D'Ath P, Katona P, Mullan E, Evans S, Katona C. Screening, detection and management of depression in elderly primary care attenders. I: The acceptability and performance of the 15 item Geriatric Depression Scale (GDS15) and the development of short versions. Fam Pract. 1994;11(3):260-6. [PubMed ID: 7843514].

  • 38.

    Malakouti SK, Fatollahi P, Mirabzadeh A, Salavati M, Zandi T. Reliability, validity and factor structure of the GDS-15 in Iranian elderly. Int J Geriatr Psychiatry. 2006;21(6):588-93. [PubMed ID: 16783767]. https://doi.org/10.1002/gps.1533.

  • 39.

    Almeida OP, Almeida SA. Short versions of the geriatric depression scale: a study of their validity for the diagnosis of a major depressive episode according to ICD-10 and DSM-IV. Int J Geriatr Psychiatry. 1999;14(10):858-65. [PubMed ID: 10521885].

  • 40.

    van den Berg E, Kloppenborg RP, Kessels RP, Kappelle LJ, Biessels GJ. Type 2 diabetes mellitus, hypertension, dyslipidemia and obesity: A systematic comparison of their impact on cognition. Biochim Biophys Acta. 2009;1792(5):470-81. [PubMed ID: 18848880]. https://doi.org/10.1016/j.bbadis.2008.09.004.

  • 41.

    The University of Waterloo. Type 2 diabetes linked to worse performance on cognitive testing. 2015. Available from: https://uwaterloo.ca/news.

  • 42.

    Crane PK, Walker R, Hubbard RA, Li G, Nathan DM, Zheng H, et al. Glucose levels and risk of dementia. N Engl J Med. 2013;369(6):540-8. [PubMed ID: 23924004]. [PubMed Central ID: PMC3955123]. https://doi.org/10.1056/NEJMoa1215740.

  • 43.

    Zhou Y, Fang R, Liu LH, Chen SD, Tang HD. Clinical Characteristics for the Relationship between Type-2 Diabetes Mellitus and Cognitive Impairment: A Cross-Sectional Study. Aging Dis. 2015;6(4):236-44. [PubMed ID: 26236545]. [PubMed Central ID: PMC4509472]. https://doi.org/10.14336/AD.2014.1004.

  • 44.

    Ramos-Rodriguez JJ, Jimenez-Palomares M, Murillo-Carretero MI, Infante-Garcia C, Berrocoso E, Hernandez-Pacho F, et al. Central vascular disease and exacerbated pathology in a mixed model of type 2 diabetes and Alzheimer's disease. Psychoneuroendocrinology. 2015;62:69-79. [PubMed ID: 26254770]. https://doi.org/10.1016/j.psyneuen.2015.07.606.

  • 45.

    Beauchet O. Testosterone and cognitive function: current clinical evidence of a relationship. Eur J Endocrinol. 2006;155(6):773-81. [PubMed ID: 17132744]. https://doi.org/10.1530/eje.1.02306.

  • 46.

    Hogervorst E, Bandelow S, Moffat SD. Increasing testosterone levels and effects on cognitive functions in elderly men and women: a review. Curr Drug Targets CNS Neurol Disord. 2005;4(5):531-40. [PubMed ID: 16266286].

  • 47.

    Janicki SC, Schupf N. Hormonal influences on cognition and risk for Alzheimer's disease. Curr Neurol Neurosci Rep. 2010;10(5):359-66. [PubMed ID: 20535591]. [PubMed Central ID: PMC3058507]. https://doi.org/10.1007/s11910-010-0122-6.