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 Table of Contents  
ORIGINAL ARTICLE
Year : 2022  |  Volume : 9  |  Issue : 2  |  Page : 100-108

Assessment of alexithymia and cognition in elderly patients with depression: A cross-sectional exploratory study


1 Department of Psychiatry, NKP Salve Institute of Medical Sciences and Lata Mangeshkar Hospital, Nagpur, Maharashtra, India
2 Department of Preventive and Social Medicine, All India Institute of Medical Sciences, Bhopal, Madhya Pradesh, India

Date of Submission12-Aug-2022
Date of Decision13-Dec-2022
Date of Acceptance22-Dec-2022
Date of Web Publication20-Jan-2023

Correspondence Address:
Dr. Abhijeet Faye
Department of Psychiatry (OPD-10), 2nd Floor, OPD Building, NKP Salve Institute of Medical Sciences and Lata Mangeshkar Hospital, Digdoh Hills, Hingna Road, Nagpur - 440 019, Maharashtra
India
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Source of Support: None, Conflict of Interest: None


DOI: 10.4103/jgmh.jgmh_41_22

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  Abstract 


Objectives: Depression is the most common psychiatric illness in the elderly. Alexithymia and cognitive impairment can be independently associated with depression and old age. This study aims to assess the alexithymia and cognitive dysfunction in geriatric patients with depression. Materials and Methods: A cross-sectional study was conducted on 100 participants of >60 years with depression. Participants were assessed using semi-structured pro forma, Geriatric Depression Scale (GDS), Hamilton Depression Rating Scale (HDRS), Toronto Alexithymia Scale-20 (TAS-20) having 3 subscales – “difficulty describing feeling” (DDF), “difficulty identifying feeling” (DIF), and “externally oriented thinking,” and Montreal Cognitive Assessment (MoCA). Statistical analysis was done using Chi-square/Fisher's exact test, Pearson's correlation, and t-test. Results: The mean age of the participants was 67.35 years with equal gender distribution. Thirty-four percent were >70 years of age and 53% from rural area. The median duration of depression was 30 months with a median duration of untreated illness, 6 months. Anxiety was the most common psychiatric comorbidity (43%). Seventy-one percent had alexithymia whereas 77% had cognitive impairment (MoCA score <26). Scores on GDS, HDRS, TAS-20, DIF, DDF, and MoCA (<26) were significantly higher in elder participants (P < 0.05) and those from rural area (P < 0.05). Higher TAS-20 score correlated with lower MoCA score (P < 0.01). Furthermore, severe depression correlated with higher TAS-20 and lower MoCA score. Conclusion: More than two-third of participants had alexithymia and cognitive dysfunction. Higher alexithymia was associated with poor cognition. Severe depression correlated with higher alexithymia and cognitive impairment. Alexithymia and cognitive dysfunction were higher in the elderly from rural region.

Keywords: Alexithymia, cognitive dysfunction, depression, elderly


How to cite this article:
Faye A, Tadke R, Gawande S, Bhave S, Kirpekar V, Chatterjee A. Assessment of alexithymia and cognition in elderly patients with depression: A cross-sectional exploratory study. J Geriatr Ment Health 2022;9:100-8

How to cite this URL:
Faye A, Tadke R, Gawande S, Bhave S, Kirpekar V, Chatterjee A. Assessment of alexithymia and cognition in elderly patients with depression: A cross-sectional exploratory study. J Geriatr Ment Health [serial online] 2022 [cited 2023 Feb 2];9:100-8. Available from: https://www.jgmh.org/text.asp?2022/9/2/100/368295




  Introduction Top


Aging is a global phenomenon, and population over 60 years of age is constantly increasing in India. It was around 7% in 2009 and expected to increase up to 20%–30% by 2050.[1] Depression is one of the most common illnesses in older adults. According to the WHO, factors responsible for increased risk of depression in older adults are chronic medical diseases and disabilities; illnesses causing pain; frustration due to restrictions in activities of daily living; personality characteristics (anxious, dependent, or avoidant); adverse events in life such as death of spouse, divorce/separation, poverty, retirement, and social isolation; and inadequate social support.[2] Studies have demonstrated the relation of depression with socioeconomic factors such as advanced age, lower education, and poverty.[3],[4]

Depression in older adults usually has a varied presentation making it difficult to diagnose.[3] It is usually associated with the increased risk of mortality (due to suicide) and morbidity, impairment in cognitive and social functioning, greater self-neglect, and impaired quality of life.[5] Among plethora of symptoms, problems related to emotional expression and cognitive dysfunction significantly affect the recovery and prognosis of depression in the elderly.

Alexithymia is a difficulty in identifying and expressing the emotions[4] along with difficulty in describing feelings and concentration on external experiences.[5] Higher alexithymia is widely noted in later life due to consistent emotional changes associated with old age.[6],[7] Alexithymia is also considered a risk factor for major depression,[8],[9] eating disorders, panic disorder, and substance use disorders.[10] Researchers found that alexithymic individuals are more exposed to the dangers of mood disorders and psychosomatic disorders as they are unable to regulate their feelings,[11] and severity of the depression.[12]

In the context of depression, cognitive dysfunctions are significantly important and include deficits in various domains such as memory, attention, executive functions, and processing speed.[13],[14] These symptoms may persist even during the remission phase of depression. Some researchers have mentioned the prevalence of cognitive problems in major depressive disorder (MDD) in the range of 85%–94% during episodes and 39%–44% during remissions.[15]

Research done on relationship of alexithymia with mild cognitive impairment (MCI) and Alzheimer's disease (AD) found that, in MCI, alexithymia was negatively correlated with working and long-term verbal memory. In AD, it was negatively correlated with attention, general cognition, memory, executive abilities, and visuospatial constructive abilities.[16] The presence of alexithymia has also been found to be associated with reduced social cognition skills, including recognition of others' emotional facial expressions.[17]

Thus, alexithymia and cognitive impairment, if present, can have a significant impact on older adults with depression, and studying these domains may give new insights into the management of depression in the elderly. With the above background, this study was planned with the aims of assessing the alexithymia and cognition in geriatric patients with depression, to find the correlation of alexithymia and cognition with sociodemographic and clinical profiles of patients, and to analyze the correlation between alexithymia and cognition in geriatric patients with depression.


  Materials and Methods Top


This was a cross-sectional study carried out in a tertiary care hospital and research center. After institutional ethics committee approval, participants were selected consecutively from the psychiatry outpatient department and indoor/ward. Considering the logistic feasibility, the sample size was decided as 100. Patients more than or equal to 60 years of age with a primary psychiatric diagnosis of MDD as per the Diagnostic and Statistical Manual of Mental Disorders, version 5 (DSM-5)/DSM-IV-TR criteria (as few patients were diagnosed before DSM-5 came in use) and willing to participate and give informed consent for the study were included. Participants excluded were those with age <60, those who had serious illness making them unable to participate, and those in delirium. Patients with intellectual disability, patients with diagnosed dementia, and patients having primary diagnosis other than depression were also excluded. New diagnosis of depression was based on DSM-5 criteria. Among already diagnosed cases, many patients were diagnosed with DSM-IV-TR. After giving detailed information about the study, participants were approached and informed consent was taken from the patients and/or family members. Each interview was conducted by trained psychiatrists in the department and took around 1 h. The study was conducted for 15-month duration from December 2020 to February 2022.

The following tools were used for the assessment:

  1. Semi-structured pro forma including sociodemographic details and clinical profile about depression (duration, symptoms, type, and diagnosis)
  2. Geriatric Depression Scale Short Form (GDS SF): GDS SF is used to measure the prevalence of depression in elderly population. The scale was first developed in 1982 by Yesavage et al. It is a 15-item scale, and questions are answered in “yes” or “no” responses. One point is assigned to each answer, and the cumulative score is rated on a scoring grid. A score of 6–10 is considered “suggestive of depression” which requires further investigation. A score of more than 10 is considered to be having a depression. Studies have shown the sensitivity and specificity of GDS SF between 70%–80% and 75%–78%, respectively, with high correlation in differentiating depressed from nondepressed. Simplicity of the scale usage enables the scale to be used with ill or moderately cognitively impaired individuals. The scale is routinely used as a part of a comprehensive geriatric mental health assessment[18]
  3. Hamilton Depression Rating Scale (HDRS): HDRS has proven to be useful for determining a patient's level of depression before, during, and after the treatment. It is administered by a clinician experienced in working with psychiatric patients. Although HDRS has 21 items, the scoring is based on the first 17. It generally takes 15–20 min to complete the interview and score the results. Eight items are scored on a 5-point scale, ranging from 0 = not present to 4 = severe. Nine are scored from 0 to 2. The total score ranges from 0 to 63 with a score <7 considered normal; 8–16, a mild depression; 17–23, a moderate depression; and >24 a severe depression. Its sensitivity is 86.4% and specificity 92.2%
  4. Toronto Alexithymia Scale-20 (TAS-20): The TAS, a 20-item instrument, is a commonly used measure of alexithymia. It has 3 subscales: (1) “difficulty describing feeling (DDF)” subscale is used to measure difficulty describing emotions. (2) “Difficulty identifying feeling (DIF)” subscale is used to measure difficulty identifying emotions, and (3) “externally oriented thinking (EOT)” subscale is used to measure the tendency of individuals to focus their attention externally. TAS-20 is a self-report scale, and items are rated using a 5-point Likert scale whereby 1 = strongly disagree and 5 = strongly agree. There are 5 items that are negatively keyed (items 4, 5, 10, 18, and 19). The total alexithymia score is the sum of responses to all 20 items, while the score for each subscale factor is the sum of the responses to that subscale. The TAS-20 uses cutoff scoring: ≤51 = nonalexithymia and ≥61 = alexithymia. Scores of 52–60 = possible alexithymia. The scale demonstrates good internal consistency (Cronbach's alpha = 0.81) and test–retest reliability (0.77, P < 0.01). Research using the TAS-20 demonstrates adequate levels of convergent and concurrent validity. The three-factor structure was found to be theoretically congruent with the alexithymia construct. In addition, it has been found to be stable and replicable across clinical and nonclinical populations[19]
  5. Montreal Cognitive Assessment (MoCA): This is a brief 30-question test requiring around 10–12 min to be completed. Scores on the MoCA range from 0 to 30, with a score of 26 and higher being considered normal. The scoring distribution is as follows:


    • Visuospatial and executive functioning: 5 points, animal naming: 3 points, attention: 6 points, language: 3 points, abstraction: 2 points, delayed recall (short-term memory): 5 points, orientation: 6 points, and score of 1 is added to the test-taker's score if he or she has 12 years or less of formal education. MoCA is a relatively simple and brief test. It helps to determine quickly whether a person has abnormal cognitive function. It has high sensitivity (>90%) and specificity (around 87%) in assessing cognitive impairment.


Statistical analysis

Data were collected using paper-based tools, and anonymized data were entered on a computer-based spreadsheet. Following entry, the data were cleaned and imported into R Studio environment for analysis. The packages “gtsummary” and “ggplot2” were used to analyze the data. Continuous variables were described with the help of their mean/median and standard deviation (SD)/interquartile range. Categorical variables were described using proportions and percentages. Appropriate tests of significance were applied to the data. Categorical variables were compared using Chi-square/Fisher's exact test and continuous variables were compared using Pearson's correlation. Continuous variables were compared along categorical data using t-test. P < 0.05 was considered statistically significant.


  Results Top


[Table 1] shows the distribution of participants as per the sociodemographic factors and clinical profile.
Table 1: Sociodemographic and clinical details

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Clinical details [Table 1]

The median duration of depression was 30 months with a median duration of untreated illness, 6 months. Majority (51%) of the participants had depression with severity in moderate range at the time of diagnosis. History of hospitalization was present in 32% (1–4 hospitalizations), and history of deliberate self-harm (DSH) attempt was present in 19% of the participants. Out of 100, 88% received combination therapy (psychotherapy and pharmacotherapy). A proportion of cases receiving diagnosis of depression (based on clinical interview and DSM-5 criteria) for the very first time were 34% whereas patients under partial remission were 38%. Nineteen percent were under complete remission. Seven percent were the resistant cases. The most common medical comorbidity was hypertension followed by hypothyroidism and diabetes mellitus (DM). The most common psychiatric comorbidity was anxiety symptoms followed by somatic symptoms. Electroconvulsive therapies were given in 21% of the participants.

The mean score for depression on GDS was 9.71 (SD = 4.03) with 71% (score >10) of the participants having depression and 10% having score in range of 6–9 indicative of “depression requiring further investigations.” On HDRS, the mean score was 12.83 (SD = 6.55) with 18% in severe range, 24% in with moderate severity, and 39% having mild depression. Nineteen percent of the participants had scores on GDS and HDRS in “no depression” range. The mean score on TAS was 65.66 (SD = 9.73) with 71% falling in “alexithymia category,” 20% in “possible alexithymia category,” and 9% in “no alexithymia” range. In alexithymia, score on DIF subscale was maximum followed by that for EOT. MoCA score was found to be <26 in 77% of the participants suggesting impaired cognition [Table 2].
Table 2: Frequency tables for Geriatric Depression Scale-15, Hamilton Depression Rating Scale, Toronto Alexithymia Scale, and Montreal Cognitive Assessment

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Correlations

Sociodemographic and clinical profile with scales scores [Table 3] and [Table 4]
Table 3: Correlations of sociodemographic/clinical profile with Geriatric Depression Scale, Hamilton Depression Rating Scale, and Toronto Alexithymia Scale-20

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Table 4: Correlations of sociodemographic and clinical profile with subscales of Toronto Alexithymia Scale-20 and Montreal Cognitive Assessment

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When scores of all the scales were compared with sociodemographic profile, it was found that score >10 on GDS, HDRS score of severe and very severe range, TAS score >61 (presence of alexithymia), DIF, DDF, mean scores, and MoCA score <26 all were significantly higher in rural participants compared to urban ones with P < 0.05 or 0.01. On comparing marital status with scores of all the scales, it was found that widows/widowers had a significantly higher score on TAS-20 (including scores on DIF and EOT) and significantly low scores on MoCA compared to those married and separated/divorced participants suggesting higher level of alexithymia and impaired cognition in widows/widowers (P < 0.05). Correlation with gender resulted in no statistical difference when scores on GDS, HDRS, TAS, and MoCA were compared in male versus female participants. Similarly, history of hospitalization did not reveal any association with scores on GDS, HDRS, TAS-20, and MoCA. Participants who received pharmacotherapy had scored significantly on GDS, HDRS, and TAS-20 total scores. Those who had moderate-to-severe depression at the time of diagnosis scored higher on GDS and HDRS now (during the study interview) also.

When continuous variables were correlated [Table 5], it was found that higher age was positively correlated with mean scores of all the scales including GAD, HDRS, and TAS-20 and its subscale DIF, DDF, and EOT and negatively correlated with score on MoCA (P < 0.01). Duration of untreated depression correlated positively with scores on HDRS, TAS-20, DIF, and DDF (P < 0.01). The longer the duration of untreated illness, the higher were the scores. EOT score also correlated positively with number of hospitalizations. The more the hospitalizations, the higher was the EOT score (P = 0.002).
Table 5: Correlation of scales scores with continuous variables

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Alexithymia and cognition

When scores on TAS-20 and MoCA were compared, a negative correlation was found, as shown in [Figure 1]. Higher score on TAS-20 was associated with lower score on MoCA, i.e., the more the alexithymia, the higher was the cognitive impairment (score < 26) [Figure 1].
Figure 1: Scatterplot comparing TAS-20 score with MoCA score. TAS: Toronto Alexithymia Scale, MoCA: Montreal Cognitive Assessment

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Severity of depression with alexithymia and cognition

On comparing the severity of depression on GDS and HDRS with TAS-20 and MoCA scores [Table 6], it was found that a higher score on GDS (>10) and severe depression on HDRS correlated positively with alexithymia on TAS-20 and MoCA score <26. This statistically significant relationship indicated that the severe the depression, the higher was the alexithymia and the more was the cognitive impairment (lower score on MoCA).
Table 6: Correlation between severity of depression and Toronto Alexithymia Scale-20 and Montreal Cognitive Assessment scores

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  Discussion Top


There is a scarcity of research on magnitude of depression in elderly population, especially in India. Some reviews and meta-analyses described that about one-third of the geriatric population suffer from depression. Second, cognitive and emotional changes accompany the aging process. Thus, depression, cognition, and alexithymia can be associated with each other. They are important as independent constructs and also when considered together. This study helps to explore this relationship.

Out of 100 elderly participants with depression, the proportion of newly diagnosed cases (based on clinical interview and DSM-5 criteria) was 34%. This finding was similar to the prevalence found in one meta-analysis of 56 community-based studies, in which authors found the prevalence as 34.4% in India.[20] However, there is a wide variation in prevalence, ranging from 6% to 80% depending on various factors such as population studied, screening tool used, and geographical area studied.[21],[22] Another study found the median prevalence rate of depression among the elderly Indian population as 21.9%.[23]

Majority of the participants were widowed, which can be explained by the age group considered in this study. There was no difference in the number of participants depending on their area of residence. This can be due to the fact that the institute, where the study was carried out, caters to both rural and urban areas. There were no gender differences in occurrence of depression, and the finding was similar to that of other studies, in which authors found almost equal gender distribution of depression.[24] However, many other studies have noted a female preponderance of depression globally.[25],[26],[27] Findings like longer duration of untreated illness and presence of moderate to severe depression in majority of the participants can be explained by the fact that, patients taking treatment in a tertiary care center are usually more chronic and severe. Also, the stigma about mental illness may still be prevalent in various regions of the country resulting in not seeking treatment on time. Furthermore, depression in the elderly many a time remains neglected or unnoticed leading to the delay in treatment. Around 20% of the participants had a history of DSH which can be explained by the severity of depression as 23% of the participants had severe depression. Thirty-two percent of the participants required psychiatric hospitalization (1–4 times). This again can be explained by moderate-to-severe level of depression, DSH attempts, medical comorbidities, and sometimes lack of family or social support. In such situations, treatment is usually more appropriate in hospital setting than at home.

Psychiatric comorbidity was found in 78% of the participants, with anxiety symptoms being most prevalent (44%) followed by somatic complaints. Some studies mention that depression commonly occurs in conjunction with other mental illnesses like anxiety disorders, somatic symptoms, pain disorder, and chronic medical illnesses like diabetes.[28] Out of 100, 44% of the participants had some medical comorbidity, hypertension being most common followed by hypothyroidism, DM, and heart disease. One Indian study found a high prevalence of comorbid physical illnesses in elderly depressed participants, with hypertension being the most common which is similar to the finding of the present study. This was followed by DM and osteoarthritis. The authors also stated that the presence of physical comorbidities was associated with frequent prescription of antidepressants such as sertraline and escitalopram.[29]

More than one-third (71%) of participants had alexithymia. Old age is associated with emotional changes, and consistent with these emotional changes, most of them have higher alexithymia score.[6],[7] This can be partly explained by the reduction in gray matter of anterior cingulate cortex[30] which is associated with the regulation of emotions. Studies also found alexithymia to be associated with many psychiatric conditions in clinical practice.[31] It can be associated with incident depression, severity, and poor response to treatment.[32],[33]

Some studies have explained that, with aging, the ability to handle emotions gets better, but in presence of alexithymia, this may not happen because of difficulty in identifying or demonstrating the feelings. This may result in ineffective coping with the stressors in life and difficulties in cognitive reappraisal.[34] One study found that people with higher alexithymia, showed frequent use of immature defenses like 'regression' and 'acting out' which are believed to affect the adaptive functioning[35] and may be responsible for developing mental illnesses like depression. These factors explain the two-way relationship of depression and alexithymia, that is, alexithymia can be more prevalent in depression as in this study and alexithymia can also be the contributing factor for occurrence of depression.

One study found that levels of alexithymia were not associated with age, gender, or education in the “over 60” age groups. The alexithymia scales “difficulties with identifying feelings” and “difficulties with describing feelings” correlated significantly with negative mood and negative body experience. In the present study also, the mean score on DIF was maximum. These results confirm the assumption that there is a connection between alexithymia and depression, and correspond to the fact that alexithymia is associated with a tendency to psychosomatic illness.[6]

Cognitive impairment was found in 77% of the participants. Studies mentioned variable estimates, but roughly, the prevalence of combined depression and cognitive dysfunction is 25% in older adults.[36] This number doubles every 5 years after the age of 70 in community residents with depression and cognitive dysfunctions. Usual cognitive impairment reported consistently in late-life depression is in episodic memory, executive functions, verbal fluency, visuospatial skills, and information processing/psychomotor speed.[37]

DSM-5 also describes cognitive dysfunctions as core symptoms of depression and includes symptoms such as difficulty in thinking and concentration and difficulty in making decisions, among the other symptoms of MDD. Cognitive symptoms, thus, should not be considered merely secondary to depression; they should be regarded at least partially as independent dimension of MDD, and an important target of treatment.[38] Some studies mention that geriatric depression is a prodrome of dementia and plays a significant role in the development of cognitive impairment lasting for long.[39] Some authors described cognitive impairment in attention, memory, language, orientation, performance, judgment, and problem-solving skill in the elderly with depression. These domains are covered in MoCA scale used in this study.[40]

In one study conducted in a nursing home among elderly persons, the prevalence of cognitive impairment was found as 75%.[41] This high prevalence can be due to the factors such as illness, physical disabilities, retirement/unemployment, loneliness, and a feeling of inability to control the environment.[42]

All scores on depression, alexithymia, and cognitive impairment were higher in participants with increasing age (among the participants). Studies show that, after the age of 60, the prevalence of cognitive impairments doubles every 5 years and more and more domains of cognition are further affected with the advancing age. Higher alexithymia and lower cognition were found in widows/widowers in this study. The finding is similar to that of other studies, with widowed individuals being more likely to be cognitively impaired than married elderly individuals.[43] Single elderly people are at greater risk of suffering dementia than married individuals.[44]

In this study, severity of depression was positively correlated with the increasing age and rural background. In a meta-analysis done by Pilania et al., the pooled prevalence of depression in the elderly was higher in rural population.[20]

Similarly, alexithymia score was also found to be higher in rural participants in this study. Some studies have found an inverse correlation of TAS-20 total score with educational level of the participants which can be indirectly related to rural area with less opportunities/awareness for education and skilled occupation.[45]

Alexithymia and cognition

In this study, higher alexithymia was found to be associated with poor cognition as per the scatter diagram. Research suggests that cognitive impairment may occur concurrently with alexithymia because of the disruption of frontal circuitry.[30] Studies show similar results of neurocognitive abilities being strongly age related and significantly inversely correlated with alexithymia total scores and individual factors.[45] Literature mentions that alexithymia is predominantly associated with the functions of right cerebral hemisphere such as visual memory and nonverbal general intelligence. This can explain that there is a common substrate for alexithymia, right hemispheric neurocognitive deficit, and age-related right hemispheric decline.[46] Sturm and Levenson found that 80% of participants with neurodegenerative disorders such as dementia scored in the alexithymic range (i.e., score of >61 on TAS-20).[47]

Neurobiological research suggests that alexithymia patients have impaired interhemispheric communication and may have dysfunctional/deficient brain structures or circuits.[48] In general population, higher alexithymia has been found to be associated with poorer performance in neurocognitive tests, mainly in memory and nonverbal intelligence. Greater alexithymia was also found to be significantly associated with poor attention, spatial reasoning, working memory, and visuospatial organization in asymptomatic HIV patients.[49] Impairment in working memory was also found in those who lack the ability to distinguish their own thoughts and feelings.[50] Thus, patients having more significant cognitive impairment were more likely to have alexithymia and positive correlation with the severity.

Alexithymia and severity of depression

Alexithymia score was significantly higher in those with severe depression. Studies also found similar results.[32] One study found that higher alexithymia was significantly associated with more severe depressive symptoms with higher scores on DIF and DDF, indicating that patients with more severe depression had greater difficulty in identifying and describing their feelings.[51]

Several studies have also mentioned that alexithymia is associated with suicidality (ideation and behavior) in general population[52],[53] which can be correlated with depression severity as suicidal risk is more with severe depression and mediates the link between alexithymia and suicide.

Alexithymia scores were found independently related to the severity of depression after controlling for factors such as demographic profile, cognition, and disease burden. This can be the attributing factor for difficulties in recognizing and expressing the negative emotions in depression and can result in the delay in seeking treatment.[51]

Furthermore, severity of depression was found to be associated with reduced score on MoCA. This can be explained as cognitive dysfunctions are among the symptom domains of depression, and impairment may increase with the severity of depressive symptoms. Second, old age is a risk factor for cognitive impairment. When “depression” and “old age” are considered together, the cognitive decline can be more prevalent and severe.

Thus, alexithymia and cognition are important constructs with respect to depression in the elderly and addressing these issues may give a better insight into the management of depression in them.


  Conclusion Top


Alexithymia and cognitive impairment were present in more than two-third of the participants and were significantly higher in older participants (the higher the age, the more was the impairment) and those from rural area. Anxiety was the most common psychiatric comorbidity. Eighteen percent of the participants had severe depression. Longer duration of untreated illness was found to be positively associated with severe depression and higher level of alexithymia. Alexithymia score was significantly higher in those with higher cognitive impairment (lower MoCA).

Implications

Alexithymia and cognition are important and related constructs to be evaluated in depth in the elderly with depression as their presence may prolong the recovery and impair the quality of life. Inverse relation between alexithymia and cognition may help future researchers to explore this relationship in detail with respect to various other associated factors (different cognitive domains, predominant depressive symptoms, influence of treatment and co-morbid other psychiatric illnesses).

Limitations

Since this was an exploratory study, no statistical correction was applied for multiple hypothesis testing. This was a cross-sectional, single-center-based study with smaller sample size. A prospective, multi-centric study may yield better results. Individual components of cognition were not studied, which would have helped in finding which cognitive functions are affected significantly in the elderly with depression. Although patients having dementia were excluded, it usually acts as a major confounding factor in cross-sectional studies on depressive disorders in the elderly.

Acknowledgments

We wish to thank all the patients and their family members, who participated, cooperated, and agreed for the publication of the data.

Financial support and sponsorship

Nil.

Conflicts of interest

There are no conflicts of interest.



 
  References Top

1.
United Nations Dept. of International Economic and Social Affairs, population Division (2010) World Population Ageing 2009. NY: United Nations; 2010.  Back to cited text no. 1
    
2.
World Health Organization. Depression and Other Common Mental Disorders: Global Health Estimates. 2017. Available from: http://apps.who.int/iris/bitstream/10665/254610/1/WHO-MSD-MER-2017.2-eng.pdf. [Last accessed on 2022 Jan 20].  Back to cited text no. 2
    
3.
Mathers CD, Loncar D. Projections of global mortality and burden of disease from 2002 to 2030. PLoS Med 2006;3:e442.  Back to cited text no. 3
    
4.
Fogley R, Warman D, Lysaker PH. Alexithymia in schizophrenia: Associations with neurocognition and emotional distress. Psychiatry Res 2014;218:1-6.  Back to cited text no. 4
    
5.
Lumley MA, Neely LC, Burger AJ. The assessment of alexithymia in medical settings: Implications for understanding and treating health problems. J Pers Assess 2007;89:230-46.  Back to cited text no. 5
    
6.
Gunzelmann T, Kupfer J, Brähler E. Alexithymia in the elderly general population. Compr Psychiatry 2002;43:74-80.  Back to cited text no. 6
    
7.
Mattila AK, Salminen JK, Nummi T, Joukamaa M. Age is strongly associated with alexithymia in the general population. J Psychosom Res 2006;61:629-35.  Back to cited text no. 7
    
8.
Taylor GJ, Bagby RM. New trends in alexithymia research. Psychother psychosom 2004;73:68-77.  Back to cited text no. 8
    
9.
Luminet O. Commentary on the paper “Is alexithymia a risk factor for major depression, personality disorder, or alcohol use disorders? A prospective population-based study”. J Psychosom Res 2010;68:275-7.  Back to cited text no. 9
    
10.
Marchesi C, Ossola P, Tonna M, De Panfilis C. The TAS-20 more likely measures negative affects rather than alexithymia itself in patients with major depression, panic disorder, eating disorders and substance use disorders. Compr Psychiatry 2014;55:972-8.  Back to cited text no. 10
    
11.
Motan I, Gençöz T. The relationship between the dimensions of alexithymia and the intensity of depression and anxiety. Turk Psikiyatri Derg 2007;18:333-43.  Back to cited text no. 11
    
12.
Saarijarvi S, Salminen JK, Toikka T. Temporal stability of alexithymia over a five-year period in outpatients with major depression. Psychother Psychosom 2006;75:107-12.  Back to cited text no. 12
    
13.
McIntyre RS, Xiao HX, Syeda K, Vinberg M, Carvalho AF, Mansur RB, et al. The prevalence, measurement, and treatment of the cognitive dimension/domain in major depressive disorder. CNS Drugs 2015;29:577-89.  Back to cited text no. 13
    
14.
Millan MJ, Agid Y, Brüne M, Bullmore ET, Carter CS, Clayton NS, et al. Cognitive dysfunction in psychiatric disorders: Characteristics, causes and the quest for improved therapy. Nat Rev Drug Discov 2012;11:141-68.  Back to cited text no. 14
    
15.
Conradi HJ, Ormel J, de Jonge P. Presence of individual (residual) symptoms during depressive episodes and periods of remission: A 3-year prospective study. Psychol Med 2011;41:1165-74.  Back to cited text no. 15
    
16.
Smirni D, Beadle JN, Paradiso S. An initial study of alexithymia and its relationship with cognitive abilities among mild cognitive impairment, mild Alzheimer's disease, and healthy volunteers. J Nerv Ment Dis 2018;206:628-36.  Back to cited text no. 16
    
17.
Di Tella M, Adenzato M, Catmur C, Miti F, Castelli L, Ardito RB. The role of alexithymia in social cognition: Evidence from a non-clinical population. J Affect Disord 2020;273:482-92.  Back to cited text no. 17
    
18.
Yesavage JA, Brink TL, Rose TL, Lum O, Huang V, Adey M, et al. Development and validation of a geriatric depression screening scale: A preliminary report. J Psychiatr Res 1982;17:37-49.  Back to cited text no. 18
    
19.
Bagby RM, Parker JD, Taylor GJ. The twenty-item Toronto alexithymia scale – I. Item selection and cross-validation of the factor structure. J Psychosom Res 1994;38:23-32.  Back to cited text no. 19
    
20.
Pilania M, Yadav V, Bairwa M, Behera P, Gupta SD, Khurana H, et al. Prevalence of depression among the elderly (60 years and above) population in India, 1997-2016: A systematic review and meta-analysis. BMC Public Health 2019;19:832.  Back to cited text no. 20
    
21.
Arumugam B, Nagalingam S, Nivetha R. Geriatric depression among rural and urban slum community in Chennai – A cross sectional study. J Evol Med Dent Sci 2013;2:795-800.  Back to cited text no. 21
    
22.
Mathias K, Goicolea I, Kermode M, Singh L, Shidhaye R, Sebastian MS. Cross-sectional study of depression and help-seeking in Uttarakhand, North India. BMJ Open 2015;5:e008992.  Back to cited text no. 22
    
23.
Barua A, Ghosh MK, Kar N, Basilio MA. Prevalence of depressive disorders in the elderly. Ann Saudi Med 2011;31:620-4.  Back to cited text no. 23
[PUBMED]  [Full text]  
24.
Goyal A, Kajal KS. Prevalence of depression in elderly population in the Southern part of Punjab. J Family Med Prim Care 2014;3:359-61.  Back to cited text no. 24
[PUBMED]  [Full text]  
25.
Girgus JS, Yang K, Ferri CV. The gender difference in depression: Are elderly women at greater risk for depression than elderly men? Geriatrics (Basel) 2017;2:35.  Back to cited text no. 25
    
26.
Brinda EM, Rajkumar AP, Attermann J, Gerdtham UG, Enemark U, Jacob KS. Health, social, and economic variables associated with depression among older people in low and middle income countries: World health organization study on global AG Eing and adult health. Am J Geriatr Psychiatry 2016;24:1196-208.  Back to cited text no. 26
    
27.
Najafipour H, Banivaheb G, Sabahi A, Naderi N, Nasirian M, Mirzazadeh A. Prevalence of anxiety and depression symptoms and their relationship with other coronary artery disease risk factors: A population-based study on 5900 residents in Southeast Iran. Asian J Psychiatr 2016;20:55-60.  Back to cited text no. 27
    
28.
Noël PH, Williams JW Jr., Unützer J, Worchel J, Lee S, Cornell J, et al. Depression and comorbid illness in elderly primary care patients: Impact on multiple domains of health status and well-being. Ann Fam Med 2004;2:555-62.  Back to cited text no. 28
    
29.
Grover S, Avasthi A, Sahoo S, Lakdawala B, Dan A, Nebhinani N, et al. Prevalence of physical comorbidity and prescription patterns in elderly patients with depression: A multicentric study under the aegis of IAGMH. J Geriatr Ment Health 2018;5:107-14.  Back to cited text no. 29
  [Full text]  
30.
Paradiso S, Vaidya JG, McCormick LM, Jones A, Robinson RG. Aging and alexithymia: Association with reduced right rostral cingulate volume. Am J Geriatr Psychiatry 2008;16:760-9.  Back to cited text no. 30
    
31.
Waller E, Scheidt CE. Somatoform disorders as disorders of affect regulation: A study comparing the TAS-20 with non-self-report measures of alexithymia. J Psychosom Res 2004;57:239-47.  Back to cited text no. 31
    
32.
Marchesi C, Bertoni S, Cantoni A, Maggini C. Is alexithymia a personality trait increasing the risk of depression? A prospective study evaluating alexithymia before, during and after a depressive episode. Psychol Med 2008;38:1717-22.  Back to cited text no. 32
    
33.
Henry JD, Phillips LH, Maylor EA, Hosie J, Milne AB, Meyer C. A new conceptualization of alexithymia in the general adult population: Implications for research involving older adults. J Psychosom Res 2006;60:535-43.  Back to cited text no. 33
    
34.
Gross JJ. The emerging field of emotion regulation: An integrative review. Rev Gen Psycho 1998;2:271-99.  Back to cited text no. 34
    
35.
Vaillant GE. Theoretical hierarchy of adaptive ego mechanisms: A 30-year follow-up of 30 men selected for psychological health. Arch Gen Psychiatry 1971;24:107-18.  Back to cited text no. 35
    
36.
Arve S, Tilvis RS, Lehtonen A, Valvanne J, Sairanen S. Coexistence of lowered mood and cognitive impairment of elderly people in five birth cohorts. Aging (Milano) 1999;11:90-5.  Back to cited text no. 36
    
37.
Morimoto SS, Kanellopoulos D, Alexopoulos GS. Cognitive impairment in depressed older adults: Implications for prognosis and treatment. Psychiatr Ann 2014;44:138-42.  Back to cited text no. 37
    
38.
Miskowiak KW, Ott CV, Petersen JZ, Kessing LV. Systematic review of randomized controlled trials of candidate treatments for cognitive impairment in depression and methodological challenges in the field. Eur Neuropsychopharmacol 2016;26:1845-67.  Back to cited text no. 38
    
39.
Muhammad T, Meher T. Association of late-life depression with cognitive impairment: Evidence from a cross-sectional study among older adults in India. BMC Geriatr 2021;21:364.  Back to cited text no. 39
    
40.
Seifaddini R, Tajadini H, Choopani R. Physiopathology of dementia from the perspective of traditional Persian medicine. J Evid Based Complementary Altern Med 2015;20:224-7.  Back to cited text no. 40
    
41.
Mirzaei M, Sepahvand E, Sahaf R, Mirzaei S, Pakdel A. The prevalence of cognitive impairment in elderly nursing home residents. J Sabzevar Univ Med Sci 2017;23:896-901.  Back to cited text no. 41
    
42.
Aajami Z, Kazazi L, Toroski M, Bahrami M, Borhaninejad V. Relationship between depression and cognitive impairment among elderly: A cross-sectional study. J Caring Sci 2020;9:148-53.  Back to cited text no. 42
    
43.
Giri M, Chen T, Yu W, Lü Y. Prevalence and correlates of cognitive impairment and depression among elderly people in the world's fastest growing city, Chongqing, People's Republic of China. Clin Interv Aging 2016;11:1091-8.  Back to cited text no. 43
    
44.
Rodríguez-Sánchez E, Mora-Simón S, Patino-Alonso MC, García-García R, Escribano-Hernández A, García-Ortiz L, et al. Prevalence of cognitive impairment in individuals aged over 65 in an urban area: DERIVA study. BMC Neurol 2011;11:147.  Back to cited text no. 44
    
45.
Onor M, Trevisiol M, Spano M, Aguglia E, Paradiso S. Alexithymia and aging: A neuropsychological perspective. J Nerv Ment Dis 2010;198:891-5.  Back to cited text no. 45
    
46.
Cabeza R. Hemispheric asymmetry reduction in older adults: The HAROLD model. Psychol Aging 2002;17:85-100.  Back to cited text no. 46
    
47.
Sturm VE, Levenson RW. Alexithymia in neurodegenerative disease. Neurocase 2011;17:242-50.  Back to cited text no. 47
    
48.
Wingbermühle E, Theunissen H, Verhoeven WM, Kessels RP, Egger JI. The neurocognition of alexithymia: Evidence from neuropsychological and neuroimaging studies. Acta Neuropsychiatr 2012;24:67-80.  Back to cited text no. 48
    
49.
Bogdanova Y, Díaz-Santos M, Cronin-Golomb A. Neurocognitive correlates of alexithymia in asymptomatic individuals with HIV. Neuropsychologia 2010;48:1295-304.  Back to cited text no. 49
    
50.
Lysaker PH, Dimaggio G, Buck KD, Carcione A, Nicolò G. Metacognition within narratives of schizophrenia: Associations with multiple domains of neurocognition. Schizophr Res 2007;93:278-87.  Back to cited text no. 50
    
51.
Bamonti PM, Heisel MJ, Topciu RA, Franus N, Talbot NL, Duberstein PR. Association of alexithymia and depression symptom severity in adults aged 50 years and older. Am J Geriatr Psychiatry 2010;18:51-6.  Back to cited text no. 51
    
52.
Alpaslan AH, Soylu N, Avci K, Coşkun KŞ, Kocak U, Taş HU. Disordered eating attitudes, alexithymia and suicide probability among Turkish high school girls. Psychiatry Res 2015;226:224-9.  Back to cited text no. 52
    
53.
Hintikka J, Honkalampi K, Koivumaa-Honkanen H, Antikainen R, Tanskanen A, Haatainen K, et al. Alexithymia and suicidal ideation: A 12-month follow-up study in a general population. Compr Psychiatry 2004;45:340-5.  Back to cited text no. 53
    


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