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Prevalence of Psychiatric Morbidity and Cognitive Impairment among Patients Attending the Rural Noncommunicable Disease Clinic
Aseem Mehra, MD Department of Psychiatry, Postgraduate Institute Medical Education and Research Chandigarh, Punjab India aseemmehra86@gmail.com
This article was originally published by Thieme Medical and Scientific Publishers Pvt. Ltd. and was migrated to Scientific Scholar after the change of Publisher.
Abstract
Abstract
Objective This study aimed to assess the prevalence of cognitive impairment and psychiatric morbidity among the patients attending the rural noncommunicable disease clinic after controlling for various confounders (i.e., psychological morbidity, obesity, gender, level of education, duration of the illness and age).
Materials and Methods One-hundred twenty-four patients were evaluated on the Hindi Mental State Examination for the cognitive function, Physical Health Questionnaire-9 for depression, and Generalized Anxiety Disorder-7 for anxiety disorders.
Results About one-fourth (26.6%) of the participants had cognitive impairment. The prevalence of cognitive impairment was more among patients with hypertension (35.5%) as compared with the diabetes mellitus (13.6%) and those with comorbid hypertension and diabetes mellitus (26.6%). About one of the participants had depression (35.5%) and 29% of the patients had anxiety disorder. No significant difference was found in the level of cognitive deficits between those with hypertension and diabetes mellitus, when the confounding factors were not taken into account in the analysis. However, after controlling for psychiatric morbidity, obesity, gender, level of education, duration of the illness and age, those with hypertension were found to have significantly higher level of cognitive impairment compared with those with diabetes mellitus. A higher level of dysfunction was seen in the domains of orientation, registration, attention, recall, language, and visuospatial domains.
Conclusion Present study suggests that patients of hypertension have higher level of cognitive impairment, when compared with those with diabetes mellitus, even after controlling for various confounders. Lack of difference between the two groups can be accounted by the confounding variables.
Keywords
cognitive impairment
noncommunicable disease
psychological morbidity
cognitive neuroscience
Introduction
Among all major health threats to emerge in the 21st century, none has challenged the foundations of public health as profoundly as the rise of chronic noncommunicable diseases (NCDs). The common NCDs include hypertension (HTN), diabetes mellitus (DM), ischemic heart diseases, cancers, osteoporosis, and chronic kidney diseases. The burden of NCDs is rising rapidly and remains among the most common cause of mortality and morbidity in the world.1 As per the World Health Organization (WHO), more than 3.6 crore death occurred each year from the NCDs with majority of the death occurring in developing countries such as India and China.2 Among the various NCDs, cardiovascular and DM are the leading causes of mortality and morbidity across the world.3 4 Looking at the current trend, by 2020, 73% of deaths and 60% of the disease will be attributable to NCDs globally.5 As per WHO, in India in cardiovascular diseases are the most common NCDs which cause deaths (24%), followed by respiratory diseases (11%), injuries (10%), and others(10%).6 Among NCDs, diabetes and HTN have a rising trend. It is projected that size of HTN group is expected to increase by 108% in India by 2050.7 8 By 2030, the number of people with diabetes will increase from 40.6 million to 79.4 million.8 9 10
Studies from across the world have shown the association between NCDs and the decline of cognitive function leading to mild cognitive impairment (MCI) or dementia.11 12 13 14 However, the etiological pathway of this relationship is not known. MCI is the transitional phase between the normal aging process and dementia.15 16 The cognitive decline can impair the quality of life and also increase the burden on the patient as well as to their caregivers, leading to more financial constraints, stigmatization, increase distress, and isolation from the society.13
Studies around the world showed that patients with NCDs reported prevalence of cognitive impairment (CI) to be 1.7 to 40%.17 18 19 Studies from India too suggest prevalence of CI to be around 4.6 to 10.8% in NCDs and have found a significant association between the NCDs and CI.11 12 13 14 16 20 In recent years, there are accumulating epidemiological evidence that HTN and diabetes are important risk factors for MCI and dementia.21 22 23 24 25 26
Research showed that midlife DM had been associated with the occurrence of CI.27 28 29 In terms of specific domains of cognitive functions, DM has been associated with impaired verbal memory, impaired attention, decreased executive function and processing and motor speed.30 31 32 The risk factors for cognitive dysfunction in DM include obesity, female gender, hyperglycemia or poor glycemic control, the extremity of age, longer duration of illness, presence of microvascular complications, presence of comorbid depression, anxiety, and HTN.14 33 34 35 36 37 38
The relationship between HTN and CI has also been documented, but findings are inconsistent, with few studies suggesting that high blood pressure (not necessarily HTN) is associated with CI39 40 and others suggest an association of CI with low blood pressure41 42 and a few suggest a “U”-shaped relationship between blood pressure and cognitive functioning.43 However, a few studies reporting no association,44 45 majority of the studies support the association of cognitive decline and HTN.46 47 48 Risk factors associated with CI include female gender, poor medication compliance, poorly controlled blood pressure, elderly age, low level of education, higher number of medication, active treatment, the type of cognitive assessment scale, presence of comorbid depression, and DM.24 49 50
Patients with NCDs have also been shown to have a high prevalence of mental disorders. In HTN, the prevalence of depression varies from 15 to 58.1%51 52 and that for anxiety disorders varies from 5 to 42.3%.51 53 The rate of depression in patients with DM ranges from 14 to 41%.54 55 Those with comorbid DM and HTN, the prevalence rate of depression and anxiety rises up to 60.9%.56 The coexistence of the NCDs and mental disorders has an important implication in terms of prognosis, quality of life, cost-effectiveness, general well-being, and expectancy of life.57 58 The presence of psychiatric illness among patients with physical illnesses leads to poor treatment adherence, poor lifestyle, increased cost of the treatment, poor quality of life, worsening of physical illness, work absenteeism, increased hospital visits, poor self-care, and higher mortality.59 60 61
Studies that have assessed CI in NCDs have not controlled for various confounding variables, such as depression, anxiety, obesity, gender, level of education, duration of the illness, and age of the participants, which can also influence cognitive functioning. Accordingly, there is a need to control for these variables to have a better understanding of the prevalence of CI among patients with NCDs. Thus, the current study aimed to evaluate prevalence of CI among patients with NCDs attending the NCD clinic at the rural health clinic (RHC) in Naraingarh, North India, after controlling for depression, age, obesity, gender, level of education, duration of the illness, and anxiety.
Materials and Methods
It was a cross-sectional study conducted among the patients attending the NCDs clinic of a community RHC run in collaboration with the Postgraduate Institute Medical Education and Research (PGIMER), Chandigarh. This clinic was established exclusively for patients suffering from diabetes mellitus, HTN, hypothyroidism, and rheumatoid arthritis. The clinic runs every Tuesday and Thursday in a rural community health center, Nariangarh. On average, 40 to 50 patients attend the clinic each day and avail the health services. The medications are available free of cost at the rural community health center. At a stretch, medications are dispensed for a maximum of 2 weeks.
A faculty member from the Department of School of Public Health, PGIMER, Chandigarh, is the in-charge of the clinic, and the services are mainly provided by a senior resident and junior residents from the Department of School of Public Health, under the supervision of the faculty member. Other staff of the NCD clinic includes the nursing staff, public health nurse, and health worker.
The study period was from June to July 2018. At the time of the beginning of the study, 208 patients were registered with the NCD clinic. A majority of patients were suffering from HTN, diabetes, or both; only a few patients diagnosed with rheumatoid arthritis or hypothyroidism.
The approval was obtained from Ethics Committee of the Institute. To be included in the study, the study participants should be ≥ 18 years old of either gender and cooperative for physical and mental status examination, who provided the written informed consent. Patients who refused to give consent and were severely ill, had a history of mental illness, were on psychotropics, or had severe visual and auditory impairment to interfere in the formal assessment were excluded.
All adult patients attending NCD clinic were approached, explained about the study, and those fulfilling the selection criteria were recruited into the study. Senior resident doctors, involved in the NCD clinic, recruited the patients and administered instruments for assessment of cognitive functions, depression, and anxiety.
Those patients who screened positive for psychiatric illness (depression, anxiety, or CI) were referred to a psychiatric out-reach outpatient clinic for further evaluation. The psychiatric out-reach outpatient's clinic runs every Wednesday by the Department of Psychiatry, PGIMER, Chandigarh, in collaboration with the Department of School of Public Health and Community Health Center of Naraingarh.
Instruments
Hindi Mental Status Examination (HMSE): Cognitive functions were assessed by using HMSE. This is designed mainly for illiterate Hindi speaking population. It can be said that this a modified version of mini-mental state examination (MMSE) with a less emphasis on calculation ability.62 It is a validated tool to evaluate cognitive decline. The sensitivity and specificity of the scale are 94 and 98%, respectively.63 64 Many researchers have used it for screening not only for dementia but also for delirium, but the authors did not present the detailed scores. Hence, the HMSE suitably adapted for the participants. In the current study, those with HMSE scores ≤ 25 were considered “cognitively impaired”64.
Patient Health Questionnaire-9 (PHQ-9): Hindi version of this tool was used to assess depression. It is a self-report questionnaire, which comprises of nine items, each evaluating the Diagnostic and Statistical Manual (DSM) of Mental Disorders criteria of depression, rated as “0” (not at all) to “3” (nearly every day). Score ≥10 has a sensitivity of 88% and a specificity of 88% for the diagnosis of major depression made by a mental health profession. We used the cutoff of 10 for making the diagnosis of depression.65
Generalized Anxiety Disorder-7 (GAD-7) scale: It is a 7-item scale with good reliability as well as a criterion, constructs, procedural, and factorial validity. Mild, moderate, and severe levels of anxiety are interpreted on the cutoff points of 5, 10, and 15. There is a good agreement between self-report and interviewer-administered versions of the scale. However, the diagnostic threshold has been reported to be a cutoff score of 10 or more. In the present study, a cutoff score of 10 or more was used to make the diagnosis of an anxiety disorder, which has been used in the previous studies.66 67
Sociodemographic profiles such as age, gender, type of family, socioeconomic status, occupation, marital status, number of years of education, and locality were recorded.
Details of the NCD, such as type of NCDs (HTN, DM, or both), duration of illness, age of onset, blood pressure, height in centimeters, weight in kilograms, were recorded. The height was measured by making the patient stand with their back against a fixed wall by using a stadiometer. The weight was measured by using a particular standard weighing machine. The blood pressure was recorded by using a mercury sphygmomanometer; the standard location of the measurement was the brachial artery.
Statistical Analysis
The statistical analysis was performed using SPSS 14.0 for Windows (SPSS for Windows, Version 14.0. Chicago, SPSS Inc., Chicago, Illinois, United States). Descriptive analysis was performed using mean and standard deviation (SD) with a range for continuous variables. Descriptive analysis was computed as frequency and percentages for discontinuous variables. For the inferential analysis, correlation analysis was done. Analysis of covariance was applied to see the relationship between the domain of the HMSE and NCDs. The dependent variables were DM, HTN, and comorbid HTN and DM. The independent variables were the mean score of the HMSE and various domains of the HMSE. The covariates were age, gender, duration of the illness, age of onset, depression, anxiety, body mass index (BMI), and education.
Results
One-hundred twenty-four participants were recruited into the present study. Mean age of the participants was 55.5 years (range: 26–90, SD: 11.9). The mean number of years of education was 5.7 (SD: 5.2). A majority of the participants were from a rural background and were not on any paid employment. About two-thirds were females. A little more than one-third (n = 48, 38.7%) patients were diagnosed with HTN only, one-sixth (N = 22; 17.7%) were diagnosed with DM only, and 54 (43.5%) patients were diagnosed with both HTN and DM. The mean BMI of the participants was 27.3 kg/m2 (Table 1).
Variables |
Mean/frequency (n = 124) |
---|---|
Age (in years) |
55.1 (11.9) |
Sex—female |
83 (66.9%) |
Marital—married |
100 (80.6%) |
Education (number of years) |
5.7 (5.2) |
Duration of illness (in months) |
63.4 (65.1) (range: 1–364) |
Occupation—not on paid employment |
90 (72.6%) |
Income (patient) |
4,394.0 (9,639.8) |
Socioeconomic status—lower/middle/upper |
65(52.4%)/55 (44.4%)/4 (3.2%) |
Type of family—extended/joint |
68 (54.8%) |
Locality—rural |
120 (96.8%) |
Primary diagnosis |
|
Hypertension |
48(38.7%) |
Diabetes Mellitus |
22 (17.7%) |
Hypertension+ diabetes mellitus |
54 (43.5%) |
Mean duration of illness (in months) |
63.4 (65.1) |
Systolic blood pressure in mm Hg |
134.5 (16.2) |
Diastolic blood pressure in mm Hg |
81.1 (10.1) |
Body mass in Index in kg/m2 |
27.3 (5.5) |
In terms of cognitive functions, the mean total score of the study sample was 26 (SD: 4.1), and 33 (26.6%) patients had HMSE score ≤24, indicating possible CI. A slightly more than one-third of the study participants were diagnosed with depressive disorder (n = 44, 35.5%) and 29% (n = 36) of the participants were diagnosed with an anxiety disorder. One-fourth of patients had both depressive and anxiety disorders. In general, CI was higher among patients with psychiatric morbidity (Table 2).
Variables |
Score (mean)[range] |
---|---|
Abbreviations: GAD, generalized anxiety disorder; HMSE, Hindi Mental State Examination; NCD, noncommunicable diseases; PHQ, patient health questionnaire. |
|
Orientation |
9.4 (1.1) [5–10] |
Registration |
2.8 (0.4) [1–3] |
Attention |
4.3 (1.1) [1–5] |
Recall |
2.2 (0.7) [0–3] |
Language |
7.4 (1.6) [3–9] |
Visuospatial |
1.6 (1.2) [0–3] |
Total |
26.0 (4.1) [12–30] |
Severity |
|
Normal (≥25) |
91 (73.4%) |
Cognitively impaired (≤ 24) |
33 (26.6%) |
HMSE score (≤ 24) |
|
Among patients with hypertension |
15 (31.25%) |
Among patients with diabetes mellitus |
3 (13.63%) |
Among patients with both hypertension and diabetes mellitus |
15 (27.77%) |
Among patients of hypertension without psychiatric morbidity |
9 (28.12%) |
Among patients of hypertension with psychiatric morbidity |
6 (37.5%) |
Among patients of diabetes mellitus without psychiatric morbidity |
1 (7.7%) |
Among patients of diabetes mellitus with psychiatric morbidity |
2 (22.22%) |
Among patients with both hypertension and diabetes mellitus and without psychiatric morbidity |
8 (26.6%) |
Among patients with both hypertension and diabetes mellitus and with psychiatric morbidity |
7 (29.16%) |
PHQ severity |
|
Normal or no depression (<10) |
80 (64.5%) |
Depression (≥10) |
44 (35.5%) |
PHQ total score |
8.3 (6.9) |
Prevalence of depression according to NCDs |
|
Hypertension (n = 48) |
14 (29.2%) |
Diabetes (n = 22) |
9 (40.9%) |
Co-morbid hypertension + diabetes mellitus (n = 54) |
21 (38.9%) |
Psychiatric morbidity in patients with hypertension |
16 (33.33%) |
Psychiatric morbidity in patients with diabetes mellitus |
9 (40.9%) |
Psychiatric morbidity in patients with hypertension and diabetes mellitus |
24 (44.44%) |
Number of patients with psychiatric morbidity |
49 (39.51%) |
GAD severity |
|
Normal or no anxiety disorder |
88 (70.96%) |
Anxiety disorder |
36 (29.0%) |
Total score |
7.0 (6.2) |
Prevalence of anxiety according to NCDs |
|
Hypertension |
14 (29.2%) |
Diabetes mellitus |
6 (27.3%) |
Comorbid hypertension+diabetes mellitus |
16 (29.7%) |
Comorbid (anxiety+ depressive) disorder |
31 (25.0%) |
Relationship of Cognitive Functions with NCDs
To assess the impact of NCDs on cognitive functions, the study sample was divided into three groups: DM (Group-I), HTN (Group-II), and those with both (Group-III). When the three groups were compared, no significant differences were seen. However, when age, gender, duration of illness, number of year of education, mean score of PHQ-9, mean score of GAD-7, and mean BMI were taken as covariates as is evident from Table 3, patients with HTN performed poorly than those with DM on all the domains of HMSE and had significantly lower HMSE score. When the combined DM and HTN group was compared with those with only DM, combined group had significantly scored low on HMSE, performed poorly on attention, language and visuospatial abilities. On the similar lines, when the combined group was compared with those with HTN only, significant differences were noted for total HMSE score and all the domains of HMSE except for recall, with patients with HTN only performing poorly than those with both HTN and DM.
Variables |
Whole group (n = 124) |
Hypertension Group I (n = 48) |
Diabetes Group II (n = 22) |
Diabetes + hypertension Group III (n = 54) |
F-Value |
p-Value |
Comparison of Group I vs. II ANCOVA F-value (p-value) |
Comparison of Group II vs. III ANCOVA F-value (p-value) |
Comparison of Group I vs. III ANCOVA F-value (p-value) |
---|---|---|---|---|---|---|---|---|---|
Abbreviations: ANCOVA, analysis of covariance; BMI, body mass index; GAD, generalized anxiety disorder; HMSE, Hindi Mental State Examination; NCD, noncommunicable diseases; PHQ, patient health questionnaire. a p < 0.001 b p < 0.05 c p < 0.01 Note: covariates = age, gender, education, duration of illness, BMI, PHQ total, GAD total. |
|||||||||
Total HMSE score |
26.0 (4.1) |
25.3 (4.3) |
27.8 (2.5) |
25.9 (4.3) |
2.894 |
II>III>I |
5.901 (<0.001)a |
2.786 (0.010b) |
4.595 (<0.001)a |
Orientation |
9.4 (1.1) |
9.2 (1.2) |
9.8 (0.5) |
9.3 (1.3) |
2.567 |
II>III>I |
3.659 (0.002)c |
1.886 (0.077) |
2.995 (0.005)c |
Registration |
2.8(0.4) |
2.7 (0.4) |
2.8 (0.4) |
2.8 (0.4) |
0.806 |
II=III>I |
2.906 (0.008)c |
1.300 (0.259) |
2.803 (0.008)c |
Attention |
4.3 (1.1) |
4.2 (1.1) |
4.7 (0.8) |
4.3 (1.2) |
2.016 |
II>III>I |
3.417 (0.003)c |
2.646 (0.014b) |
2.967 (0.005)c |
Recall |
2.2 (0.7) |
2.0 (0.7) |
2.5 (0.5) |
2.1 (0.7) |
5.055 |
II>Ic II>IIIb III>I |
2.779 (0.011)b |
1.513 (0.169) |
1.842 (0.079) |
Language |
7.4 (1.6) |
7.2 (1.7) |
7.9 (1.2) |
7.3 (1.6) |
1.431 |
II>III>I |
5.987 (<0.001)a |
4.109 (<0.001)a |
5.371 (<0.001)a |
Visuospatial |
1.6 (1.2) |
1.5 (1.3) |
2.0 (1.0) |
1.6 (1.2) |
1.229 |
II>III>I |
6.483 (0.001)a |
3.651 (0.001)c |
5.029 (<0.001)a |
Discussion
In developing countries such as India, the prevalence of NCDs and the elderly population is increasing rapidly. Despite these facts, so far, CI in patients with NCDs largely remains neglected. The present study shows prevalence of CI in patients with NCDs was 26.6%, the prevalence of depression was 35.5%, and that of anxiety disorder was 29%. One-fourth of patients had both depressive and anxiety disorders. Previous studies from India, which have evaluated prevalence of CI in elderly (aged >65 years) by using the HMSE or modified MMSE, report prevalence to vary from 3.5 to 11.5%.63 68 69 70 71 72 However, none of these studies have been done specifically among the subjects with NCDs. Findings of the current study are compared with these studies, and it is evident that prevalence of CI is more in patients with NCD. Existing data from other parts of the world suggest that the prevalence of dementia in patients with NCD ranges from 2.34 to 38.6%73 74 75 76 77 78 and the current study also reported within range. Among patients with DM, the prevalence of CI in the present study was 13.63%. Previous studies from India, which have assessed CI in DM, have reported prevalence rates of 11.6,13 13.7 to 16.9,9 and 33.7%,12 respectively; present study also reported within the range. Similarly, prevalence of CI among patients with HTN in the present study was 31.2%. Previous studies from India, which were conducted among patients with HTN, have reported prevalence rates of reported 11.913 and 13%,79 respectively. Findings of the present concur with the available literature. Prevalence of CI among those with both DM and HTN was 26.6%, and this is also supported by the existing literature, which suggests higher prevalence rates when patients have both illnesses.49 80 81 These findings suggest that patients with NCDs form a high-risk group for CI and dementia. Accordingly, there is a need to screen these patients routinely for cognitive functioning, and these patients must be provided information about the development of CI, factors contributing to the same, lifestyle changes, and cognitive exercises to prevent CI and early detection.
In the present study, psychiatric morbidity was found in 39.51% of the patients, with depression in 35.5% and anxiety disorder in 29.9% of cases, with a majority of them having comorbid depression and anxiety. These prevalence figures are in the reported range in the available literature for psychiatric morbidity among patients with NCD, DM, and HTN from India and abroad.82
The present study also supports the existing literature that prevalence of CI is higher in the presence of psychiatric morbidity in the form of depression and anxiety disorders.14 38
Very few studies have compared the CIs among patients with DM, HTN, and both, after controlling for various confounding variables. In the present study, after controlling for the covariates (age, gender, duration of illness, number of year of education, mean score of PHQ-9, mean score of GAD-7, and BMI) when patients of HTN and DM were compared, patients with HTN were found to have significantly higher level of CI. Further, the higher level of dysfunction was seen in the domains of orientation, registration, attention, recall, language, and visuospatial domains. These findings suggest that HTN possibly has a more negative impact on cognitive functions when compared with DM.
When patients with DM were compared with those with both DM and HTN, those with both the illnesses had higher impairment in the form of lower HMSE score, impairment in attention, language, and visuospatial domains. Similarly, when HTN group was compared with those with both HTN and DM, those with both the illnesses had higher impairment in the form of lower HMSE scores and lower scores in all the domains, except recall. These findings provide preliminary evidence about the differential effect of DM and HTN on cognitive functions.
A small sample size limits the present study. Only HMSE was used to screen for a cognitive profile, which has its limitations. Psychiatric morbidity was evaluated by using PHQ-9 and GAD-7, and the mental health professionals did not confirm the diagnosis. The assessment was cross-sectional. The study did not asses the cognitive profile before the illness, and hence, it cannot be said that the level of cognitive deficits noted can be attributed to the NCDs only. The study did not evaluate the course of the NCDs and fluctuation in the symptoms. Similarly, other factors, such as dietary patterns and lifestyle, were not assessed. The study did not have a comparative group without NCDs.
To conclude, the present study suggests that about one-fourth of patients with NCD have CI and 39.51% have psychiatric morbidity. The present study also suggests that prevalence of CI is higher among patients of NCD with psychiatric morbidity. When severity and prevalence of CI are compared between patients of HTN and diabetic, it was seen that prevalence and severity of cognitive deficits are higher among patients with HTN. Hence, it can be said that patients with NCDs should be routinely screened for cognitive functioning and these patients must be provided information about the development of CI, factors contributing to the same, lifestyle changes and cognitive exercises to prevent CI and early detection. Similarly, these patients must also be routinely screened for psychiatric morbidity and this must be treated adequately.
Conflict of Interest
None declared.
References
- Cardiovascular disease risk factors in Asian Indian population: a systematic review. J Cardiovasc Dis Res. 2013;4(4):222-228.
- [Google Scholar]
- World Health Organisation. World Health Day; 2017. Available at: http://www.who.int/campaigns/world-health-day/2017/ en. Accessed June 29, 2020
- The top 10 causes of death. Mediacenter, Factsheets: World Health Organization (WHO); 2016. Available at: https://www.who.int/news-room/fact-sheets/detail/the-top-10-causes-of-death
- Evaluation of automated hepatitis C core antigen assay in occupational exposure. Pathology. 2013;45(5):529-531.
- [Google Scholar]
- World Health Organization. World report on disability. 2011
- Hypertension in India: a systematic review and meta-analysis of prevalence, awareness, and control of hypertension. J Hypertens. 2014;32(6):1170-1177.
- [Google Scholar]
- Global burden of hypertension: analysis of worldwide data. Lancet. 2005;365:217-223. (9455)
- [Google Scholar]
- Diabetes mellitus: a risk factor for cognitive impairment amongst urban older adults. Ind Psychiatry J. 2012;21(1):44-48.
- [Google Scholar]
- High prevalence of diabetes and impaired glucose tolerance in India: National Urban Diabetes Survey. Diabetologia. 2001;44(9):1094-1101.
- [Google Scholar]
- Prevalence and pattern of cognitive dysfunction in type 2 diabetes mellitus. Int J Med Appl Sci. 2013;2:246-252.
- [Google Scholar]
- The prevalence and predictors of cognitive impairment in type 2 diabetic population of Punjab, India. J Soc Health Diabetes. 2017;5:47-53.
- [Google Scholar]
- Screening for mild cognitive impairment among noncommunicable disease patients attending a rural primary health center in Puducherry, South India. J Nat Sci Biol Med. 2019;10:77-81.
- [Google Scholar]
- An epidemiologic study of mild cognitive impairment in Kolkata, India. Neurology. 2007;68(23):2019-2026.
- [Google Scholar]
- Prevalence, distribution, and impact of mild cognitive impairment in Latin America, China, and India: a 10/66 population-based study. PLoS Med. 2012;9(2):e1001170.
- [Google Scholar]
- Cognitive impairment and hypertension in older adults living in extreme poverty: a cross-sectional study in Peru. BMC Geriatr. 2017;17(1):250.
- [Google Scholar]
- The prevalence of cognitive impairment amongst type 2 diabetes mellitus patients at Abakaliki South-East Nigeria. J Metab Syndr. 2015;4:171.
- [Google Scholar]
- Mild cognitive impairment and depressive symptoms in elderly patients with diabetes: prevalence, risk factors, and comorbidity. J Diabetes Res. 2014;2014:179648.
- [Google Scholar]
- Prevalence of functional cognitive impairment and associated factors in Brazilian community-dwelling older adults. Dement Neuropsychol. 2017;11(1):32-39.
- [Google Scholar]
- Vascular contributions to cognitive impairment and dementia: a statement for healthcare professionals from the American Heart Association/American Stroke Association. Stroke. 2011;42(9):2672-2713.
- [Google Scholar]
- Risk of dementia in diabetes mellitus: a systematic review. Lancet Neurol. 2006;5(1):64-74.
- [Google Scholar]
- Smoking, hypercholesterolaemia and hypertension as risk factors for cognitive impairment in older adults. Age Ageing. 2013;42(3):306-311.
- [Google Scholar]
- Impaired cognitive executive dysfunction in adult treated hypertensives with a confirmed diagnosis of poorly controlled blood pressure. Int J Med Sci. 2014;11(8):771-778.
- [Google Scholar]
- Subjective cognitive failures in patients with hypertension are related to cognitive performance and cerebral microbleeds. Hypertension. 2014;64(3):653-657.
- [Google Scholar]
- Impact of nocturnal heart rate variability on cerebral small-vessel disease progression: a longitudinal study in community-dwelling elderly Japanese. Hypertens Res. 2015;38(8):564-569.
- [Google Scholar]
- Cognitive decline and dementia in diabetes–systematic overview of prospective observational studies. Diabetologia. 2005;48(12):2460-2469.
- [Google Scholar]
- Diabetes in midlife and cognitive change over 20 years: a cohort study. Ann Intern Med. 2014;161(11):785-793.
- [Google Scholar]
- Type 2 diabetes as a risk factor for dementia in women compared with men: a pooled analysis of 2.3 million people comprising more than 100,000 cases of dementia. Diabetes Care. 2016;39(2):300-307.
- [Google Scholar]
- A meta-analysis of cognitive functioning in nondemented adults with type 2 diabetes mellitus. Can J Diabetes. 2014;38(6):401-408.
- [Google Scholar]
- Magnitude of cognitive dysfunction in adults with type 2 diabetes: a meta-analysis of six cognitive domains and the most frequently reported neuropsychological tests within domains. J Int Neuropsychol Soc. 2014;20(3):278-291.
- [Google Scholar]
- Assessing premorbid cognitive ability in adults with type 2 diabetes mellitus–a review with implications for future intervention studies. Curr Diab Rep. 2014;14(11):547.
- [Google Scholar]
- Diabetes mellitus and Alzheimer’s disease: shared pathology and treatment? Br J Clin Pharmacol. 2011;71(3):365-376.
- [Google Scholar]
- Brain insulin resistance and deficiency as therapeutic targets in Alzheimer’s disease. Curr Alzheimer Res. 2012;9(1):35-66.
- [Google Scholar]
- Edinburgh Type 2 Diabetes Study Investigators. Diabetic retinopathy and cognitive decline in older people with type 2 diabetes: the Edinburgh Type 2 Diabetes Study. Diabetes. 2010;59(11):2883-2889.
- [Google Scholar]
- Investigation on the relationship between diabetes mellitus type 2 and cognitive impairment. Diabetes Res Clin Pract. 2008;82(3):305-309.
- [Google Scholar]
- Type 2 diabetes mellitus contributes to cognitive decline in old age: a longitudinal population-based study. J Int Neuropsychol Soc. 2004;10(4):599-607.
- [Google Scholar]
- Impact of diabetes on cognitive function and brain structure. Ann N Y Acad Sci. 2015;1353:60-71.
- [Google Scholar]
- The age-dependent relationship between blood pressure and cognitive impairment: a cross-sectional study in a rural area of Xi’an, China. PLoS One. 2016;11(7):e0159485.
- [Google Scholar]
- Blood pressure and performance on the Mini-Mental State Examination in the very old. Cross-sectional and longitudinal data from the Kungsholmen Project. Am J Epidemiol. 1997;145(12):1106-1113.
- [Google Scholar]
- Association between blood pressure and cognitive function in a biracial community population of older persons. Neuroepidemiology. 2002;21(3):123-130.
- [Google Scholar]
- Nonlinear relations of blood pressure to cognitive function: the Baltimore Longitudinal Study of Aging. Hypertension. 2005;45(3):374-379.
- [Google Scholar]
- Correlates of incident cognitive impairment in the REasons for Geographic and Racial Differences in Stroke (REGARDS) Study. Clin Neuropsychol. 2015;29(4):466-486.
- [Google Scholar]
- Cognitive status, stroke symptom reports, and modifiable risk factors among individuals with no diagnosis of stroke or transient ischemic attack in the REasons for Geographic and Racial Differences in Stroke (REGARDS) Study. Stroke. 2007;38(4):1143-1147.
- [Google Scholar]
- Hypertension severity is associated with impaired cognitive performance. J Am Heart Assoc. 2017;6(1):e004579.
- [Google Scholar]
- Midlife hypertension and 20-year cognitive change: the atherosclerosis risk in communities neurocognitive study. JAMA Neurol. 2014;71(10):1218-1227.
- [Google Scholar]
- Fourteen-year longitudinal study of vascular risk factors, APOE genotype, and cognition: the ARIC MRI Study. Alzheimers Dement. 2009;5(3):207-214.
- [Google Scholar]
- Comorbid type 2 diabetes mellitus and hypertension exacerbates cognitive decline: evidence from a longitudinal study. Age Ageing. 2004;33(4):355-361.
- [Google Scholar]
- Cognitive function and blood pressure control in hypertensive patients over 60 years of age: COGNIPRES study. Curr Med Res Opin. 2008;24(12):3331-3339.
- [Google Scholar]
- Anxiety and depression among hypertensive outpatients in Afghanistan: a cross-sectional study in Andkhoy City. Int J Hypertens. 2018;2018:8560835.
- [Google Scholar]
- Prevalence of depression in patients attending general medicine outpatient department for hypertension. Int J Med Sci Public Health. 2019;8(2):105-109.
- [Google Scholar]
- Prevalence of risk factors for non-communicable diseases in the adult population of urban areas in Kabul City, Afghanistan. Cent Asian J Glob Health. 2014;2(2):69.
- [Google Scholar]
- Depressive symptoms among participants with type 2 diabetes in Southeast Asia: a systematic review. J Diabetol. 2018;9:19-24.
- [Google Scholar]
- Depression and associated factors among the patients with type 2 diabetes in Rwanda. Ethiop J Health Sci. 2019;29(6):709-718.
- [Google Scholar]
- Suresh Kumar K. Prevalence of common mental disorders among patients with diabetes mellitus and hypertension in an urban east Delhi slum - a cross sectional study. TJP. 2015;1(1):27-31.
- [Google Scholar]
- A study of association of depressive symptoms among the type 2 diabetic outpatients presenting to a tertiary care hospital. Indian J Psychol Med. 2012;34(1):30-33.
- [Google Scholar]
- Prevalence of depression in a large urban South Indian population–the Chennai Urban Rural Epidemiology Study (CURES-70) PLoS One. 2009;4(9):e7185.
- [Google Scholar]
- Depression in type 2 diabetes mellitus–a brief review. Diabetes Metab Syndr. 2014;8(1):62-65.
- [Google Scholar]
- The impact of type 2 diabetes on health related quality of life in Bangladesh: results from a matched study comparing treated cases with non-diabetic controls. Health Qual Life Outcomes. 2016;14(1):129.
- [Google Scholar]
- “Mini-mental state”. A practical method for grading the cognitive state of patients for the clinician. J Psychiatr Res. 1975;12(3):189-198.
- [Google Scholar]
- A Hindi version of the MMSE: the development of a cognitive screening instrument for a largely illiterate rural elderly population in India. Int J Geriatr Psychiatry. 1995;10:367-377.
- [Google Scholar]
- Hindi Mental State Examination (HMSE) as a screening test for illiterate demented patients. Int J Geriatr Psychiatry. 2000;15(7):662-664.
- [Google Scholar]
- The PHQ-9: validity of a brief depression severity measure. J Gen Intern Med. 2001;16(9):606-613.
- [Google Scholar]
- A brief measure for assessing generalized anxiety disorder: the GAD-7. Arch Intern Med. 2006;166(10):1092-1097.
- [Google Scholar]
- Dropout rates and reasons for dropout from treatment among elderly patients with depression. J Geriatr Ment Health. 2018;5:121-127.
- [Google Scholar]
- Prevalence of cognitive impairment and related factors among elderly: a population-based study. J Dr NTR Univ Health Sci. 2013;2:171-176.
- [Google Scholar]
- Prevalence and correlates of cognitive impairment in a north Indian elderly population. WHO South-East Asia J Public Health. 2014;3(2):135-143.
- [Google Scholar]
- Prevalence of dementia in an urban population in Kerala, India. Br J Psychiatry. 2005;186:136-140.
- [Google Scholar]
- An epidemiological study of dementia among the habitants of eastern Uttar Pradesh, India. Ann Indian Acad Neurol. 2011;14(3):164-168.
- [Google Scholar]
- Prevalence of dementia among Kashmiri migrants. Ann Indian Acad Neurol. 2008;11(2):106-108.
- [Google Scholar]
- Prevalence of and risk factors for cognitive impairment among elderly without cardio- and cerebrovascular diseases: a population-based study in Rural China. Front Aging Neurosci. 2018;10:62.
- [Google Scholar]
- The prevalence of mild cognitive impairment with type 2 diabetes mellitus among elderly people in China: a cross-sectional study. Arch Gerontol Geriatr. 2016;62:138-142.
- [Google Scholar]
- Prevalence of dementia and main subtypes in rural northern China. Dement Geriatr Cogn Disord. 2015;39:294-302. (5-6)
- [Google Scholar]
- A comparison of the prevalence of dementia in the United States in 2000 and 2012. JAMA Intern Med. 2017;177(1):51-58.
- [Google Scholar]
- Prevalence of cognitive impairment in recently diagnosed type 2 diabetes patients: are chronic inflammatory diseases responsible for cognitive decline? PLoS One. 2015;10(10):e0141325.
- [Google Scholar]
- Diabetes is not associated with Alzheimer’s disease neuropathology. J Alzheimers Dis. 2017;60(3):1035-1043.
- [Google Scholar]
- Blood pressure and cognitive impairment in India and the United States: a cross-national epidemiological study. Arch Neurol. 2003;60(8):1123-1128.
- [Google Scholar]
- The relationship of hypertension in the elderly to AD, vascular dementia, and cognitive function. Neurology. 2002;58(8):1175-1181.
- [Google Scholar]
- NIDDM and blood pressure as risk factors for poor cognitive performance. The Framingham Study. Diabetes Care. 1997;20(9):1388-1395.
- [Google Scholar]
- Co-existing non-communicable diseases and mental illnesses amongst the elderly in Punjab, India. Eur Endocrinol. 2019;15(2):106-112.
- [Google Scholar]