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ORIGINAL ARTICLE |
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Year : 2020 | Volume
: 21
| Issue : 1 | Page : 43-49 |
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Impact of stressful life events in mood disorders
Ooha Susmita Biddala1, Rayapureddy Satya Krishna Kumar2, P Krishna Mohan3, Savithri Bhavaraju4
1 Post-Graduate, Department of Psychiatry, Pinnamaneni Siddhartha Institute of Medical Sciences and Research Foundation, Vijayawada, Andhra Pradesh, India 2 Assistant Professor, Department of Psychiatry, Pinnamaneni Siddhartha Institute of Medical Sciences and Research Foundation, Vijayawada, Andhra Pradesh, India 3 Professor and HOD, Department of Psychiatry, Pinnamaneni Siddhartha Institute of Medical Sciences and Research Foundation, Vijayawada, Andhra Pradesh, India 4 MSc Statistics, Department of Community Medicine, Pinnamaneni Siddhartha Institute of Medical Sciences and Research Foundation, Vijayawada, Andhra Pradesh, India
Date of Submission | 10-Feb-2020 |
Date of Decision | 18-Feb-2020 |
Date of Acceptance | 29-Mar-2020 |
Date of Web Publication | 03-Jul-2020 |
Correspondence Address: Dr. Rayapureddy Satya Krishna Kumar Department of Psychiatry, Pinnamaneni Siddhartha Institute of Medical Sciences and Research Foundation, Vijayawada - 521 286, Andhra Pradesh India
 Source of Support: None, Conflict of Interest: None
DOI: 10.4103/AMH.AMH_12_20
Background: Life events are defined as discrete experiences that disrupt an individual's usual activities, causing a substantial change and readjustment, such as marriage, physical illness or death in the family. A temporal relationship has been established between such stressful life events and the onset and severity of psychiatric illness in many studies. Aims: To assess the impact of stressful life events in patients with mood disorders. Materials and Methods: 70 patients with an established diagnosis of an affective disorder according to ICD-10 were sampled via consecutive sampling. Sociodemographic proforma and HAM-D or YMRS were applied as relevant to rate the severity of illness. Presumptive stressful life events scale (PSLES) was applied to assess for the number and score of stressful life events during the patient's lifetime and the past one year. Results: Stressful life events were found to have a significant contribution to the illness in the context of the socio-demographic background of the subjects. Significant correlation was also seen between severity of illness and stress scores from PSLES with events occurring over lifetime, desirable events and impersonal events eliciting a more severe illness. Conclusion: Life events can behave as acute and ongoing stressors during the course of an illness. Establishing their impact and addressing coping mechanisms should be done to make for a comprehensive management of any patient diagnosed with a mood disorder.
Keywords: Bipolar disorder, depression, mood disorders, stressful life events
How to cite this article: Biddala OS, Krishna Kumar RS, Mohan P K, Bhavaraju S. Impact of stressful life events in mood disorders. Arch Ment Health 2020;21:43-9 |
Introduction | |  |
According to the World Health Organization's 10th edition of International Classification of Diseases (ICD-10), the spectrum of mood disorders spans from unipolar depression to bipolar affective disorder (BPAD) to persistent mood disorders such as dysthymia.[1] According to the National Mental Health Survey conducted by Gururaj et al. in 2015, 2.9% of psychiatric patients are diagnosed with a mood disorder making it one of the most common mental illnesses in the country.[2] Their neurobiology however has complex underpinnings of gene–environment interactions. One such environmental factor which is known to affect the course of the disease (irrespective of the genetic load) is stressful life events (SLEs).[3]
Life events are defined as discrete experiences that disrupt an individual's usual activities, causing substantial change and readjustment, such as marriage, physical illness, or death in the family.[4] In the presumptive stressful life events scale (PSLES) validation study by Singh et al., he recorded that an average individual of the Indian population experiences ten SLEs in his lifetime (10.34 ± 5.40) and approximately two SLEs over the period of 1 year (1.90 ± 2.62) without suffering any adverse effects as a result of it.[5]
SLEs can be of negative or positive valence. Negative life events such as childhood adversity, physical trauma, death of a loved one, have been found to be one of the strongest predisposing factors for a mood disorder, especially depression.[6],[7] A review by Johnson found the rates of negative life events in the periods prior to unipolar and bipolar depression to be comparable to each other and higher than during control periods in the studies included.[8] They were also found to be predictors of increased affective symptoms in a longitudinal study by Johnson et al.[9] This was an extension of previous studies which had reported such a result only in predisposed subgroups, i.e., female bipolar patients and patients with negative cognitive styles.[10],[11] Singh et al. also reported in their study that participants perceived more stress for negative (undesirable) life events in comparison to desirable events.[5]
However, positive life events like marriage have also been associated with triggering an affective episode.[6] Their impact was seen to be more in patients of BPAD than depression in a study by Johnson et al. who reported that positive goal-attainment events were predictive of increases in manic symptoms.[12] Overall, it was noted in multiple studies that schedule disrupting events had more impact over the current episode irrespective of their valence.[13],[14]
Studies have also suggested that a greater number of SLEs is associated with a more recurrent course of illness.[15],[16] However, during the course of the illness, life events may be caused as a direct result of the individual's behavior (due to mental illness) and lead to recurrences. Such events may be described as dependent life events.[17] A strong association was established between such events and risk for depressive disorders with an odds ratio of 5.85 for females and 4.55 for males in an epidemiological study by Kendler and Gardner [18] Another study by Williamson et al. found adolescents with depression were at a higher risk for experiencing dependent SLEs as was the case for patients of BPAD in a study by Bender et al.[19],[20] On the other hand, Kemner et al. found a robust influence of independent life events on recurrent admissions in BPAD even after controlling for dependent SLEs.[21]
Further highlighting the role of SLEs in the course of mood disorders is the close temporal relationship often observed between the onset of an episode and a recent SLE. Various studies clarified the window of increased vulnerability to being 1 month following an SLE for unipolar depression to 3 weeks for a relapse of BPAD to 3 months prior in patients who have committed suicide.[22],[23],[24] Studies have also recorded patients with more SLEs in the past year presenting with greater severity of symptoms and requiring a longer time to recover.[16],[25]
The association between SLEs and mood disorders, if understood, can be targeted for pharmacological and nonpharmacological interventions.[16] However, only a handful of studies have assessed the relationship between life events and mood disorders in India. Furthermore, very little of the existing literature has addressed this association in the context of the sociodemographic background of the patient which by itself may contribute to the illness.[6]
This research is undertaken with the primary objective of studying the impact of SLEs in patients presenting with mood disorders to the psychiatry outpatient department (OPD) of a tertiary care hospital.
Materials and Methods | |  |
It was a cross sectional study undertaken in Pinnamaneni Siddhartha Institute of Medical Sciences, Vijayawada, Andhra Pradesh, India between August 2018 and January 2019. All the patients with mood disorders attending the psychiatry OPD constituted the population of the study.
Inclusion criteria
- Patients who met the diagnostic criteria for mood disorders according to ICD-10.
Exclusion criteria
- History of significant chronic medical illness
- History of comorbid substance misuse disorders other than nicotine dependence
- History of other diagnosed psychiatric illnesses
- Patients who are uncooperative
- Patients who did not give consent to take part in the study.
Sample collection
Consecutive sampling was done to include every patient diagnosed with a mood disorder.
Period of study
August 2018 to January 2019 (6 months).
Measurements used
- Hamilton Rating Scale for Depression (HAM-D)
- Young's Mania Rating Scale (YMRS)
- PSLES [5]
- ICD-10.
Procedure
This study was undertaken following approval from the institutional ethical committee. Patients were explained about the study and informed consent was taken. Appropriate ethical approval procedures were followed while taking consent from subjects and also in conducting the research. Sociodemographic details were collected using a semi-structured pro forma developed in the Department of Psychiatry. HAM-D or YMRS was applied as relevant to rate the severity of illness after diagnosis had been made according to ICD-10 criteria. PSLES was applied to assess for the number and score of SLEs during the patient's lifetime and the past 1 year.
Statistical analysis
ANOVA was done to study the association between the SLEs and the selected variables. Binary logistic regression was done to assess for impact of SLEs in relation to other sociodemographic variables. P ≤0.05 was considered statistically significant. Statistical package for social sciences (SPSS), version 21.0, released in 2012 by IBM corp, Armonk, New York, United States of America was used for analysis.
Results | |  |
Seventy patients presenting during the study and meeting the inclusion criteria were taken as patients.
Sociodemographic profile
The sociodemographic profile of the patients is shown in [Table 1]. The mean age was 38.71 years (standard deviation = 11.82 years), with a preponderance of women (65.7%) in the sample. The majority originated from a rural background (64.3%), belonged to middle class socioeconomically (60%), were married (71.4%), and living in a nuclear family setup (78.6%). Although most patients had attained a secondary level of education (41.4%), home-making and unemployment were found to be the most prevalent (37.1% and 27.1% respectively).
Clinical profile of patients
The clinical profile of the patients diagnosed with a mood disorder is shown in [Table 2]. Forty-five (64.3%) of the patients were diagnosed with a depressive disorder, whereas 25 (35.8%) were diagnosed with BPAD. Severity of depression assessed with HAM-D revealed the majority of patients to be suffering from moderate depression followed by severe depression. Mania was rated on YMRS and found 56.3% of the patients to be having severe illness.
Stressful life events
The average number of SLEs, as summarized in [Table 3], experienced by a subject with a mood disorder was 7 (±3) within the year prior to the current episode and 8 (±3) over their lifetime. Undesirable events were found to be greater in number (7 ± 3) than desirable events (5 ± 2). | Table 3: Descriptive statistics of stressful life events experienced by the subjects
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Total accumulated stress score among the individuals was around 652.8 points, with undesirable events adding up to a greater average of 365.14 points.
Patients with depressive disorders were found to have experienced slightly more SLEs on an average (15 ± 4) with greater accumulated stress scores (676.27) than patients with bipolar disorder (14 ± 4 and 610.56).
Impact of stressful life events
Binary logistic regression
Binary logistic regression analysis was done to assess the impact of SLEs in the context of patients' sociodemographic variables. The results are shown in [Table 4] and [Table 5]. The number of SLEs and stress experienced were found to make a significant contribution to the illness (P = 0.016 and 0.032, respectively). | Table 4: Impact of number of stressful life events in the context of sociodemographic variables
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Further analysis with the events divided by time of occurrence revealed SLEs across lifetime to be contributory in the sociodemographic context with P = 0.029 and 0.011 for number of events and stress score, respectively.
Analysis of variance
The association of SLEs with the severity of mood disorder was assessed using ANOVA and the results are shown in [Table 6].
The severity of depression was found to have a correlation with number of SLEs experienced and stress accumulated within the past 1 year (P = 0.001 and 0.01, respectively) and also during the patient's lifetime (P < 0.001). The most common events experienced within the last year were illness of self or family followed by conflicts with family members and change in sleeping patterns. While the number of desirable (P < 0.001) and impersonal (P = 0.004) events were significant, the stress accrued through undesirable events was also found to be associated with severity (P < 0.001).
Manic symptoms, on the other hand, were found to have a correlation with total number of events and the amount of stress experienced (P < 0.001). However, when categorized by time, only the events over lifetime were found significant (P < 0.001). Both desirable (P = 0.01 and 0.004) and undesirable events (P < 0.001) seemed to play a role, and with regards to personal and impersonal events, while the number of personal events did not have a significance, the stress accumulated due to them did (P = 0.03).
Discussion | |  |
The major findings of our study are: (a) SLEs have an impact in the course of a mood disorder which is significant and independent of the sociodemographic background of the patient; (b) SLEs accrued over a lifetime have a stronger association with mood disorders over events in the past year; (c) desirable SLEs also influence depression along with undesirable events; and (d) impersonal life events are correlated with both depressive and manic spectra of affective disorders.
In the study by Singh et al., during the development of the PSLES questionnaire, they found that an average individual can experience up to 10 events in his lifetime with no adverse effects.[5] The average number of events experienced by the patients in our study was 14. Interpreting the results of logistic regression, the greater number of stressful experiences appears to have led to adverse consequences for the individuals in the study, which was independent of the impact due to other socioeconomic factors. The contribution by SLEs was found to be more than or almost equivalent to that due to other well-established associations such as age, employment status, family type, and socioeconomic status. A similar correlation was found by Hassanzadeh et al. in their community-based study and Mandelli et al. in women.[26],[27] Koenders et al. also noted this association in patients of bipolar disorder I and II with stronger influence in Type I.[28]
In the stress–diathesis hypothesis, diathesis is explained as a predisposing factor that goes beyond genetic vulnerability and includes cognitive and social predispositions.[29] In such diathetic individuals, an additive contribution of stress has been proposed to result in psychopathology.[30] This additive component could explain the finding in our study that stress accrued over a lifetime influences the illness and its severity more than the events of the past 1 year.
The sensitization theory of the kindling model might also be used to explain this finding.[31] Over the course of illness, a patient might require only a lessor stressor to become symptomatic given the sensitization of neural pathways to stress accumulated in life previously.[32] This is further supported by the work of Hlastala et al. who found that the effect of exogenous factors like life events in depression does not decay with time as was suggested by some older studies and by Seedat et al. reporting in his community-based study that distal life events have a significant and independent effect on the disorder.[33],[34]
SLEs overall were also found to be significantly associated with severity of mania in our study. This is in accordance with previous research by Sam et al. who reported greater BPRS scores in bipolar patients with pre-onset SLEs, Kemner et al. who found a greater risk of admission with increasing life event load and Hosang et al. who noted the higher frequency of adverse life events prior to a patient's worst episode.[21],[35],[36]
Depression, on the other hand, was found to have strong association with desirable life events. Events categorized as desirable included marriage of self or a daughter, entry of a new family member, buying or building a house or moving to a new home, going on a trip, starting a new business and pregnancy or birth of a daughter. All of these events inherently bring about a major change in one's lifestyle and routine which requires renewed adjustment and realignment. This is corroborated by the fact that one of the most common events reported by the patients in our study was change in sleep patterns over the previous year.
Social rhythm disruption hypothesis of depression talks about such occurrences in vulnerable individuals and their tendency, in them, to result in depression due to their inability to reverse the disruption and maintain the state of instability.[37] This theory was also borne out by the findings of Malkoff-Schwartz et al. and Aktekin et al. who reported a higher frequency of schedule-disrupting events in their patients.[38],[39] As undesirable events might also be reasonably expected to cause a disruption in schedule, the finding in our study that stress caused due to undesirable events was correlated with severity of illness despite the lack of such interaction with number of undesirable SLEs further lends credence to the theory.
In patients with both manic and depressive symptoms, our study found a significant correlation with events categorized as impersonal. Events included under this heading were characterized by existing or occurring beyond the control of the patient (e.g., death of a loved one, lack of a son, failure in an examination) as opposed to personal events wherein the patient had a role to play (marital conflict, sexual problems, starting a new business). This is in accordance with previous studies which noted a similar pattern.[23],[36]
The advantage of our study was that it was designed to analyze the impact of life events on mood disorders in the context of an Indian socio-cultural background which has hardly been done in the country. SLEs in our study were measured using a scale that had been particularly developed and validated for application on the Indian population. Furthermore, the inclusion of both unipolar and bipolar spectra of illness provided an opportunity to assess for variations and overlap in the presentation of affective disorders.
However, our study is also limited by the smaller sample size and the lack of an effective healthy control group. Patients with psychotic symptoms were excluded from the study due to their inability to participate effectively. Other variables such as interval to onset of illness from the occurrence of life event, number of previous episodes, and family history were not included. Furthermore, recall bias and dependent life events could also have contributed to the confounding factors.
Conclusion | |  |
The main findings in our study are (i) SLEs influence mood disorder in a comparable manner to variables such as age, socioeconomic status, employment, and type of family unit, and (ii) The presence of SLEs might result in greater severity of the affective episode. Therefore, approach to the illness and the therapeutic process should integrate not only the sociodemographic profile but also the recent and lifetime stressors experienced by the patient.
Further research can also be undertaken to differentiate the impact of dependent and independent life events in the course of a mood disorder and to assess whether this knowledge can be applied to prophylactic measures employed in the course of treatment.
Financial support and sponsorship
Nil.
Conflict of interest
There are no conflict of interest.
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[Table 1], [Table 2], [Table 3], [Table 4], [Table 5], [Table 6]
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