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The Prevalence of Cognitive Impairment Amongst Type 2 Diabetes Mellitus Patients at Abakaliki South-East Nigeria
Chukwuemeka O Eze*1, Basil C Ezeokpo1, Uma A Kalu1 and Ikenna O Onwuekwe2
1Department of Medicine, Federal Teaching Hospital Abakaliki (FETHA), Ebonyi State, Nigeria
2Department of Medicine, University of Nigeria Teaching Hospital (UNTH), Enugu, Nigeria

Abstract
Type 2 Diabetes Mellitus (DM) could be associated with cognitive impairment. The spectrum of cognitive impairment ranges from mild deficits that are not clinically detectable to the most severe clinical form, dementia. Some of the potential mechanisms include the effects of brain infarcts, white matter disease, hyperinsulinaemia, advanced glycosylated end products, and Lipoprotein Related Proteins (LRP). There is limited data on the prevalence of cognitive impairment amongst type 2 DM patients in south - east Nigeria. Therefore, this study was undertaken to determine the prevalence of cognitive impairment in type 2 DM patients attending a diabetic clinic in Abakaliki south-east Nigeria. It is a cross-sectional, descriptive and hospital based study carried out over a three months period (October 2013 to September 2014). Mini Mental State Examination (MMSE) was used for cognitive functions assessment and interpreted as follows; a score of 25-30 as normal, and ≤24 as cognitive impairment. The data was analyzed using Statistical Package for Social Sciences (SPSS) version 19 software. Out of 499 type 2 DM patients that were screened for the study, 450 were eligible for the study with male to female sex ratio of 2 (190): 3 (260). The age range was 30-89 years with mean age of 59.43±9.28 years. One hundred and eighty (40%) patients had cognitive impairment with male to female sex distribution of 55 (28.9%) and 125 (48.1%) respectively. Advanced age, low education attainment, unskilled occupation and presence of diabetic complications were the identified risk factors for cognitive impairment. Mini mental state examination should be a frequent tool in routine assessment of diabetic patients as it is simple and sensitive in detecting cognitive impairment. Also, identified modifiable risk factors should be corrected.
Keywords
Abakaliki; Cognitive Impairment; Nigeria; Prevalence; Type 2 Diabetes Mellitus

Introduction
Diabetes mellitus currently assumes a pandemic status, with global prevalence of 366 million in 2011 and an expected rise to 552 million by 2030 [1]. It is the second most common non-communicable disease in Nigeria [2]. Type 2 Diabetes Mellitus (DM2) is associated with cognitive impairment [3]. The spectrum of cognitive impairment ranges from mild deficits that are not clinically detectable to the most severe clinical form, dementia. Epidemiological studies have shown that DM2 patients have a twofold increased risk of developing either vascular dementia or Alzheimer’s disease [3,4].

Both cognitive impairment and DM2 are disorders that are more common in the elderly. This co-occurrence could mean that the processes that lead to DM2 also cause cognitive impairment or that cognitive impairment is a result of complications of DM2. Some of the potential mechanisms of cognitive impairment in DM2 include the effects of brain infarcts, white matter disease, hyperinsulinaemia, advanced glycosylated end products, and Lipoprotein Related Proteins (LRP) [5]. In addition, diabetes has been associated with increased deposition and decreased clearance of beta amyloid [6]. Furthermore, poor glycemic control and chronic episodes of hypo- or hyperglycemia may lead to microangiopathy, neuronal loss, and cognitive impairment [7]. Finally, diabetes is associated with macro- and microvascular cerebral disease [7], all of which may independently increase the risk of cognitive impairment.

This study was conducted at a tertiary health facility in Abakaliki South-east Nigeria. Abakaliki is the capital of Ebonyi state which has only one tertiary health facility. This hospital recieves referral from the state which has a population of about 4,339,136 and its environs. However, the pattern of cognitive impairment in DM2 patients in this area is not known. Therefore, this study was undertaken to determine the prevalence of cognitive impairment in DM2 patients attending a diabetic clinic in a tertiary hospital in Abakaliki. This will help fill the knowledge gap and also create baseline data for comparison with future studies.
Results
Out of 499 DM2 patients that were screened for the study, 450 were eligible for the study with male to female sex ratio of 2 (190): 3 (260). The age range was 30- 89years with mean age of 59.43±9.28 years. The sex and age distribution was shown in table 1. One hundred and eighty (40%) patients had cognitive impairment with male to female sex distribution of 55 (28.9%) and 125 (48.1%) respectively. There was statistically significant association between cognitive impairment and patient’s age at diagnosis of DM2, low education attainment, unskilled occupation, presence of DM complications and advanced patients age. The association of cognitive impairment with demographics and clinical features were shown in tables 2 and 3.
Discussion
Cognitive impairment as defined [10] by MMSE ≤24 was noted in 44% of the DM2 patients studied. This prevalence rate was high when compared to some other hospital based studies [11,12], but closely approximates 36% reported in India [13]. The difference could come from the varying tools for assessment of cognitive functions used in the studies and also the socio-demographics of the study populations. For instance, about 60% of the study population had primary or no formal education.

Slightly less than half (47%) of the female patients had cognitive impairment as compared to less than a third of their male counterpart (31%). This difference is statistically significant (p=0.0005). This is similar to the report of Zhang et al., [11] This could result from early deprivation from formal education, perhaps lowering their brain “reserve”, allowing the symptoms of cognitive impairment to appear at an earlier date during disease progression as alluded to by Zhang et al., [11] Also the effects of female sex hormones could not be excluded [14]. Oestrogens are known to be a protective factor in development of cognitive impairment and most of the female patients in this study were postmenopausal.

There was statistically significant association between cognitive impairment and advanced patients age, low education attainment, unskilled occupation, and the presence of DM complications.

Advanced (≥65 years) age is associated with increased prevalence of cognitive impairment. This has multiple explanations. First, advanced age is a very strong independent risk factor for development of cognitive impairment. Ageing process is characterized by the deposition of some insoluble protein metabolic products like senile plaques which results in neuronal death by apoptosis. This induces cerebral atrophy and attendant cognitive impairment [11]. Also, the preponderance of other risk factors for cognitive impairment in advanced age like stroke, dyslipidaemia, hypertension and cardiac diseases are also implicated.

Low education attainment was associated with higher prevalence of cognitive impairment. Illiteracy is an independent risk factor for cognitive impairment as the brain is not well developed resulting in reduced cognitive reserve. Also, illiterates are usually more involved in unhealthy lifestyle practices like smoking and excessive use of alcoholic drinks. Furthermore, they may be involved in unhealthy feeding habits and may not have access to adequate medical care. All these increase their risk of developing cognitive impairment. This finding is similar to the report in China [11].

Unskilled occupation like peasant farming was associated with higher prevalence of cognitive impairment. This is because those involved in unskilled occupation are mainly illiterates and those with mental retardation. They did not have the privilege of formal education or could not cope with the rigors of formal education and of skilled occupation. This is also similar to the report of Zhang et al., [11].

The presence of complications of DM was associated with cognitive impairment. Evidence suggests that the pathogenesis of cognitive impairment in DM2 is similar to that of the chronic diabetic complications [5-7]. This then makes it invariable to expect cognitive impairment whenever other chronic complications of DM2 are present.

There is no significant association between duration of DM2, presence of hypertension and family history of DM with cognitive impairment. DM2 is usually diagnosed several years after the actual onset of the disease. This is because of apparent subclinical manifestation of early DM2 for several years. In other words, the duration from point of diagnosis is gross under estimation of the correct duration. This makes it an unreliable means of classification of DM2.

It is surprising that there was no significant association between hypertension and cognitive dysfunction owing to the fact that hypertension is an independent risk factor [15]. This could result from the number of the study population which is relatively small though it was calculated using WHO formula for sample size in a finite population. Also the effects of the confounding variables could not be excluded as about 60% of the study population were illiterates.
Conclusion
The prevalence of cognitive impairment is high amongst DM2 patients seen at Abakaliki south east Nigeria with female preponderance. Advanced age, low education attainment, unskilled occupation and presence of DM complications were the identified risk factors. MMSE should be a frequent tool in routine assessment of diabetic patients as it is simple and sensitive. There should be legislation on compulsory female education in order to reduce the impact of illiteracy on their cognition. Also, modifiable risk factors should be corrected if present as management of severe cognitive impairment is rather disappointing.
Acknowledgement
We wish to acknowledge the staff of the medical records department of Federal Teaching Hospital Abakaliki for retrieving the data for the study.

References
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Tables
Age range (years) Male n (%) Female n (%) Total n (%)
30- 39 7 (1.56) 27 (6.00) 34 (7.56)
40- 49 30 (6.67) 54 (12.00) 84 (18.67)
50-59 44 (9.78) 85 (18.89) 129 (28.67)
60-69 81 (18.00) 63 (14.00) 144 (32.00)
70-79 24 (5.33) 24 (5.33) 48 (10.66)
80-89 4 (0.89) 7 (1.56) 11 (2.44)
Total 190 (42.23) 260 (57.77) 450 (100)
Table 1: The sex and age distribution.

Cognitive functionVariable

  Normal n (%) Impaired n (%) Chi-square df p- value
Sex Male 132 (29.33) 58 (12.89) 12.30 1 0.0005
Female 138 (30.67) 122 (27.11)      
Age <65 yrs 195 (43.33) 100 (22.22) 13.29 1 0.0003
≥65 yrs 75 (16.67) 80 (17.78)      
Education None 9 (2.00) 68 (15.11) 180.00 3 < 0.0001
Primary 79 (17.56) 98 (21.78)      
Secondary 62 (13.78) 5 (1.11)      
Tertiary 120 (26.67) 9 (2.00)      
Occupation Civil servant 120 (26.67) 29 (6.44) 82.67 3 < 0.0001
Trader 78 (17.33) 59 (13.11)      
Farmer 24 (5.33) 74 (16.44)      
Artisan 48 (10.67) 18 (4.00)      
Family history of DM2 Absent 169 (37.56) 126 (28.00) 2.62 1 0.1050
Present 101 (22.44) 54 (12.00)      
Age at onset of DM2 <40 yrs 96 (21.33) 57 (12.67) 0.73 1 0.3935
≥40 yrs 174 (38.67) 123 (27.33)      
≥5 yrs 169 (37.56) 114 (25.33)      
Table 2: Cognitive function and demographics of the study population.

  Cognitive function
Variable   Normal n (%) Impaired n (%) Chi-square df p- value
FBG <110 64 (14.22) 36 (8.00) 0.86 1 0.3546
≥110 206 (45.78) 144 (32.00)      
CXS absent 138 (30.67) 32 (7.11) 51.05 1 < 0.0001
Present 132 (29.33) 148 (32.89)      
BP normal 211 (46.89) 143 (31.78) 0.11 1 0.7420
High 59 (13.11) 37 (8.22)      
Drugs Metformin only 94 (20.89) 69 (15.33) 0.58 1 0.4467
Metformin and Daonil 176 (39.11) 111 (24.67)      
Table 3: Cognitive functions and the clinical features of the study population.
FBG-Fasting Blood Glucose; CXS-Complications; BP-Blood Pressure
Citation: Eze CO, Ezeokpo BC, Kalu UA, Onwuekwe IO (2015) The Prevalence of Cognitive Impairment Amongst Type 2 Diabetes Mellitus Patients at Abakaliki South-East Nigeria. J Diabetes Metab Syndr Disord 2: 003.