|Year : 2021 | Volume
| Issue : 1 | Page : 26-29
A study of cerebrovascular risk factors in depressive patients in old age
Pyare Lal Bhalothia1, Paramjeet Singh1, Banwari Lal Mawlia2, Sahiba Singh3, Priyank Jain4
1 Department of Psychiatry, SMS Medical College and Attached Hospital Jaipur, Jaipur, Rajasthan, India
2 Department of Psychiatry, Government District Hospital, Jalore, Department of Internal Medicine, Whitesberg Lexington US
3 ARH, Whitesberg Lexington, US, USA
4 Department of Psychiatry, RVRS Medical College, Bhilwara, Rajasthan, India
|Date of Submission||19-Dec-2018|
|Date of Decision||30-Mar-2019|
|Date of Acceptance||19-Jan-2021|
|Date of Web Publication||05-Aug-2021|
Dr. Pyare Lal Bhalothia
SR, Department of Psychiatry, SMS Medical College and Attached Hospital Jaipur, Jaipur, Rajasthan
Source of Support: None, Conflict of Interest: None
Context: Depression in late life is more likely to be associated with multiple medical comorbidities and cognitive impairment. In old-age hypertension, hyperlipidemia and obesity have been associated with cognitive impairment and vascular depression. The severity of vascular burden has a positive correlation with the severity of depression. Aims: This study aimed to find the association between cerebrovascular risk factors (CVRFs) and depression in old age. Methodology: A cross-sectional observational study was carried out at the outpatient department (OPD) of psychiatric center, SMS Medical College and Hospital, Jaipur. The patients from the OPD who provided informed consent were the participants in this study. Two hundred cases of depressive episode or recurrent depressive episode (unipolar depression) were included in the study. The diagnosis was made as per the International Classification of Diseases-10 criteria by two psychiatrists independently. Framingham CVRF prediction tool was applied to assess vascular burden. This was followed by statistical analysis. Results: The mean age of participants were 68.53 years, the mean score of Hamilton Depression Rating Scale (HAM-D) was 19.10 and the mean score of CVRFs was 13.13. HAM-D score positively correlates with CVRFs score (r = 0.188 and P = 0.008). Conclusions: Our study contributes to the growing literature elucidating the relationship of CVRFs in depressed older adults confirming that greater vascular burden can contribute to the severity of depression in geriatric depression.
Keywords: Cerebrovascular risk factors, depression, old age
|How to cite this article:|
Bhalothia PL, Singh P, Mawlia BL, Singh S, Jain P. A study of cerebrovascular risk factors in depressive patients in old age. J Geriatr Ment Health 2021;8:26-9
|How to cite this URL:|
Bhalothia PL, Singh P, Mawlia BL, Singh S, Jain P. A study of cerebrovascular risk factors in depressive patients in old age. J Geriatr Ment Health [serial online] 2021 [cited 2022 Jan 27];8:26-9. Available from: https://www.jgmh.org/text.asp?2021/8/1/26/323111
| Introduction|| |
Depression among older adults (in individuals 60 years and above) is broadly defined as late-life depression (LLD). It is associated with several public health concerns, including increased mortality rates, physical disability, functional decline, increased health-care utilization, and increased suicide rate. Depression in late life is more likely to be associated with multiple medical comorbidities and cognitive impairment. In old-age hypertension, hyperlipidemia and obesity have been associated with cognitive impairment and vascular depression. [3,4] The vascular depression hypothesis suggests that a large subgroup of people with major depression has concomitant occult neurologic disorders with vascular etiologies (i.e., stroke and/or vascular disease risk factors). National Mental Health Survey of India, 2015–16, reported higher rates of depression among the elderly (3.5%). There is clear-cut evidence of an association between depression and diseases such as vascular disease, upper gastrointestinal disease, lower gastrointestinal disease, hepatobiliary disease, neurological disease (primarily stroke and Parkinsonism More Details), and endocrine-metabolic disease (primarily diabetes) in various studies. It can be concluded from the available literature that medical illness can be both a cause and a consequence of depression and that treatment of depression can have a positive effect on quality of life, functioning, and health of an individual. Some other studies demonstrated that elderly patients with depression could be divided into two subgroups, early-onset depressives and late-onset depressives. Early-onset depressives had its initial onset earlier in life and there was a recurrence of a disorder in late life. Late-onset depressives had onset of depression for the first time in late life. Early-onset depression was characterized by a higher rate of depression among first-degree relatives indicating genetic risk for depression in this group. The late-onset depressives had an excess of other factors, especially chronic medical illness, suggesting that physical illness could play an important role in the pathogenesis of those depressions that occur for the first time in later life.,, Structural neuroimaging studies have noted increased cortical and central atrophy in older depressed patients, as compared with normal elderly subjects,,, a finding consistent with brain parenchymal damage. Finally, most,,, but not all magnetic resonance imaging studies have shown greater diffuse T2-weighted hyperintensities in older depressed patients than in age-matched control subjects, and these hyperintensities were associated with the presence of cerebrovascular risk factors (CVRFs).,,,,,,
Vascular risk factors can lead to cerebrovascular disease through several mechanisms including atherosclerosis, oxidative stress, cerebral hemorrhages, and infarcts. The severity of vascular burden has a positive correlation with the severity of depression.
Aim and objectives
This study aimed to find the association between CVRFs and depression in older adults.
| Methodology|| |
A cross-sectional hospital-based study was carried out at the outpatient department of psychiatric center, SMS Medical College and Hospital, Jaipur. The study included 200 cases of depressive episode or recurrent depressive episode (unipolar depression). Informed consent was obtained from all subjects prior to participate in the study. To recruit for the study, subjects were screened for the following inclusion criteria such as diagnosis of depressive episode or recurrent depressive episode (unipolar depression) as per the International Classification of Diseases (ICD) 10 criteria, 60 years or older patient of either gender, Hamilton Depression Rating Scale (HAM-D) score of 15 or higher, Mini-Mental State Examination (MMSE) score of 26 or higher, and patients willing to participate in the study. Patients with a history of any other psychiatric Illness or substance abuse (other than tobacco), comorbid medical illness, acutely suicidal or violent behavior, and electroconvulsive therapy in the last year were excluded from the study. Permission for ethical clearance was obtained from the local ethical body of the institution. After recruitment, cases were subjected to detailed assessment which included demographic details, anthropometric measurements, standard clinical assessment comprising of historical details, symptoms, physical examination, and other health issues.
The diagnosis was made as per the ICD-10 criteria by two psychiatrists independently. Those patients who satisfied the screening process were recruited for the study. Then, each participant in the study was subjected to instruments of the study. HAM-D was used to assess depression. The HAM-D is a 17-item scale that evaluates depressed mood, vegetative and cognitive symptoms of depression, and comorbid anxiety symptoms. The 17 items are rated on either a 5-point (0–4) or a 3-point (0–2) scale. In general, the 5-point scale items use a rating of 0 = absent; 1 = doubtful to mild; 2 = mild to moderate; 3 = moderate to severe; and 4 = very severe. A rating of 4 is usually reserved for extreme symptoms. The 3-point scale items used a rating of 0 = absent; 1 = probable or mild; and 2 = definite. There is some consensus for interpretation of the total scores: very severe, >23; severe, 19–22; moderate, 14–18; mild, 8–13; and no depression, 0–7.
Mini-Mental Status Examination Scale
It was used to test the individual's orientation, attention, calculation, recall, language, and motor skills. Total number of correct responses in the scale will be the total score. The individual can receive a maximum score of 30 points.
Framingham cerebrovascular risk factor prediction tool
It was used to assess cerebrovascular risk. It predicts vascular burden in both men and women separately on the basis of performance on the following risk factors: age, systolic blood pressure, the use of antihypertensive therapy, diabetes mellitus, cigarette smoking, history of atrial fibrillation, and left ventricular hypertrophy by electrocardiogram. [20,21]
| Results|| |
Data were analyzed using the Statistical Package of the Social Sciences SPSS version 19 IBM New York. Descriptive statistics were expressed as mean, standard deviation (SD), and frequency (percentage) as appropriate. To study the relationship between CVRFs and severity of depression, we estimated Pearson's correlation coefficient. Age was not included as a separate covariance because it was used to calculate the CVRFs' score. The mean age of the study sample was 68.53 years. The level of significance was set at P < 0.05.
In our study, sociodemographic profile of the studied population showed that of 200 subjects, 65.5% (131) were male and 34.5% (69) were female. About 78.5% (157) were Hindu and 21.5% (41) were Muslim. Nearly 54.5% (109) were from urban background and 45.5% (91) were from rural background. Seventy-seven percent (154) were married and 21% (42) were widowed. Sixty-four percent (128) belonged to nuclear extended family, 18% (36) to joint family, and 18% (36) belonged to nuclear family. Nine percent (18) were educated up to primary standard, 20.5% up to middle standard, 30% (60) up to secondary standard, 16% (32) up to higher secondary, 17% (34) up to graduate or postgraduate, and 7.5% (15) had a professional degree or diploma. About 17.5% (35) were unemployed, 15% (30) were unskilled workers, 22% (44) were skilled workers, 13.5% (27) were clerk or shop owners, and 16% (32) were professional workers.
[Table 1] shows that MMSE score of the sample was ranged from 26 to 30, the mean score was 28.59 with SD of 1.17, HAM-D (17 items) score ranged from 15 to 27 and mean was 19.10 with SD of 2.936, and CVRFs' score of the study population was ranged from 4 to 25 with a mean of 13.13 and SD 5.6.
|Table 1: Scores of mini-mental state examination, Hamilton Rating Scale for depression and correlation between cerebrovascular risk factors in study population|
Click here to view
[Table 2] shows that HAM-D score positively correlate with CVRFs score (r = 0.188 poor positive significant correlation and P = 0.008), i.e., as HAM D score of depression increases, CVRF score of cerebrovascular disease also increases by using Pearson correlation coefficient.
|Table 2: Correlation between cerebrovascular risk factors score and hamilton rating scale for depression-17 item score|
Click here to view
| Discussion|| |
As shown in [Table 1], the MMSE score ranged from 26 to 30 and the mean score was 28.59 with SD of 1.179. Similar to our study, Schneider et al. 2012 conducted a study to evaluate the relationship between vascular burden and pattern of cognitive impairment in older adults with depression. In their study, the mean of MMSE score of the sample was 29.1 (range from 26 to 30, SD = 1.2). [Table 1] shows that the HAM-D (17 items) score ranged from 15 to 27 and the mean was 19.10 with SD of 2.936. Similarly, Schneider et al. 2012 also found that the mean of HAM-D score was 17.4 (range from 15 to 25, SD = 2.0) in their study. [Table 1] shows that the CVRFs score ranged from 4 to 25 with a mean of 13.13 and SD of 5.6. Similar to our study, Schneider et al. 2012 also found the mean of CVRFs score was 11.1 (range from 3 to 26, SD = 5.1). Hence, our study results are similar to previous studies in terms of severity of depression, severity of cerebrovascular burden, and MMSE score.
As shown in [Table 2] and by [Graph 1], the HAM-D score positively correlated with CVRFs score (r = 0.188 and P = 0.008). Similarly, Schneider et al. 2012 found that depression severity was significantly associated with CVRFs score (r = 0.22 and P = 0.03) and this finding was consistent with the finding of Mast et al. 2004 who examined longitudinal support for the vascular depression hypothesis by assessing 100 consecutive geriatric rehabilitation patients. Elderly people are probably vulnerable to depression, and cardiovascular disease, diabetes mellitus, high cholesterol levels, and other such diseases increase the risk for LLD. [23,24] Review studies indicate a higher frequency of depression in older people with cardiovascular disease with or without a cerebrovascular component and suggest the possibility of a bidirectional relationship between vascular disease and depression, although the association between vascular risk factors and LLD may not be consistent and the causality in the individual case may be difficult to establish. The authors hence concluded that greater vascular burden was positively associated with depressive symptoms over a period of time.
Our study has several limitations. This study design was cross-sectional that precludes establishing an etiologic relationship between CVRFs, depression, and cognition. Further longitudinal study is required to establish this relationship. In our study, the sample size was relatively small which predominantly included male, educated, and relatively healthy older adults which limits the generalizability of the results. We excluded individuals based on comorbid substance use, neurological disorder, and other psychiatric disorder. These exclusionary criteria may exclude some real-world patients with depression.
| Conclusions|| |
The study contributes to the growing literature elucidating the relationship of CVRFs in depressed older adults confirming that greater vascular burden can contribute to the severity of depression in geriatric depression. Geriatric depressed patients are prone to vascular risk factors and poor cognitive functioning. Our current study can be particularly useful in identifying clinical markers related to depression risk, which may be useful to clinicians seeking to identify those patients most likely to present with depression in medical settings.
Financial support and sponsorship
Conflicts of interest
There are no conflicts of interest.
| References|| |
Steffens DC, Otey E, Alexopoulos GS, Butters MA, Cuthbert B, Ganguli M, et al
. Perspectives on depression, mild cognitive impairment, and cognitive decline. Arch Gen Psychiatry 2006;63:130-8.
Lebowitz BD, Pearson JL, Schneider LS, Reynolds CF 3rd
, Alexopoulos GS, Bruce ML, et al
. Diagnosis and treatment of depression in late life. Consensus statement update. JAMA 1997;278:1186-90.
Cui X, Lyness JM, Tu X, King DA, Caine ED. Does depression precede or follow executive dysfunction? Outcomes in older primary care patients. Am J Psychiatry 2007;164:1221-8.
Bhalla RK, Butters MA, Becker JT, Houck PR, Snitz BE, Lopez OL, et al
. Patterns of mild cognitive impairment after treatment of depression in the elderly. Am J Geriatr Psychiatry 2009;17:308-16.
Alexopoulos GS, Meyers BS, Young RC, Campbell S, Silbersweig D, Charlson M. 'Vascular depression' hypothesis. Arch Gen Psychiatry 1997;54:915-22.
STENSTEDT A. Involutional melancholia: An etiologic, clinical and social study of endogenous depression in later life, with special reference to genetic factors. Acta Psychiatr Neurol Scand Suppl 1959;127:1-71.
Hopkinson G. A genetic study of affective illness in patients over 50. Br J Psychiatry 1964;110:244-54.
Mendlewicz J. The age factor in depressive illness: Some genetic considerations. J Gerontol 1976;31:300-3.
Kumar A, Miller D, Ewbank D, Yousem D, Newberg A, Samuels S, et al
. Quantitative anatomic measures and comorbid medical illness in late-life major depression. Am J Geriatr Psychiatry 1997;5:15-25.
Rabins PV, Pearlson GD, Aylward E, Kumar AJ, Dowell K. Cortical magnetic resonance imaging changes in elderly inpatients with major depression. Am J Psychiatry 1991;148:617-20.
Zubenko GS, Sullivan P, Nelson JP, Belle SH, Huff FJ, Wolf GL. Brain imaging abnormalities in mental disorders of late life. Arch Neurol 1990;47:1107-11.
Coffey CE, Wilkinson WE, Weiner RD, Parashos IA, Djang WT, Webb MC, et al
. Quantitative cerebral anatomy in depression. A controlled magnetic resonance imaging study. Arch Gen Psychiatry 1993;50:7-16.
Lesser IM, Miller BL, Boone KB, Hill-Gutierrez E, Mehringer CM, Wong K, et al
. Brain injury and cognitive function in late-onset psychotic depression. J Neuropsychiatry Clin Neurosci 1991;3:33-40.
Figiel GS, Krishnan KR, Doraiswamy PM, Rao VP, Nemeroff CB, Boyko OB. Subcortical hyperintensities on brain magnetic resonance imaging: A comparison between late age onset and early onset elderly depressed subjects. Neurobiol Aging 1991;12:245-7.
Coffey CE, Figiel GS, Djang WT, Saunders WB, Weiner RD. White matter hyperintensity on magnetic resonance imaging: Clinical and neuroanatomic correlates in the depressed elderly. J Neuropsychiatry Clin Neurosci 1989;1:135-44.
Flicker L. Cardiovascular risk factors, cerebrovascular disease burden, and healthy brain aging. Clin Geriatr Med 2010;26:17-27.
Schneider B, Ercoli L, Siddarth P, Lavretsky H. Vascular burden and cognitive functioning in depressed older adults. Am J Geriatr Psychiatry 2012;20:673-81.
Hamilton MA. Rating scale for depression. J Neurol Neurosurg Psychiatry 1960;23:56-62.
Rovner BW, Folstein MF. Mini-mental state exam in clinical practice. Hosp Pract (Off Ed) 1987;22:99-110.
Wolf PA, D'Agostino RB, Belanger AJ, Kannel WB. Probability of stroke: A risk profile from the Framingham study. Stroke 1991;22:312-8.
Wolf PA, Dawber TR, Thomas HE Jr., Kannel WB. Epidemiologic assessment of chronic atrial fibrillation and risk of stroke: The Framingham study. Neurology 1978;28:973-7.
Mast BT, Neufeld S, MacNeill SE, Lichtenberg PA. Longitudinal support for the relationship between vascular risk factors and late-life depressive symptoms. Am J Geriatr Psychiatry 2004;12:93-101.
Naismith SL, Norrie LM, Mowszowski L, Hickie IB. The neurobiology of depression in later-life: Clinical, neuropsychological, neuroimaging and pathophysiological features. Prog Neurobiol 2012;98:99-143.
Thomas AJ, Kalaria RN, O'Brien JT. Depression and vascular disease: What is the relationship? J Affect Disord 2004;79:81-95.
Kales HC, Maixner DF, Mellow AM. Cerebrovascular disease and late-life depression. Am J Geriatr Psychiatry 2005;13:88-98.
[Table 1], [Table 2]