|Year : 2016 | Volume
| Issue : 8 | Page : 59-63
The effects of sociodemographic factors on depression management
Joshua Wednesday Edefo1, Waka Tony Udezi2
1 Department of Pharmacy, Federal NeuroPsychiatric Hospital, Uselu, Nigeria
2 Department of Clincal Pharmacy and Pharmacy Practice, University of Benin, Benin City, Nigeria
|Date of Web Publication||3-Jan-2017|
Joshua Wednesday Edefo
Department of Pharmacy, Federal Neuro Psychiatric Hospital, Uselu, P.M.B. 1008, Benin
Source of Support: None, Conflict of Interest: None
Objective: To explore the effect of sociodemographic factors on response rate to antidepressants therapy in depression management. Methods: A prospective study design of 6 follow-ups per patient after the initial contact was employed. Follow-up was done every 4 weeks for up to the 24 th week per patient that completed the study. Degree of depression was determined using the International Classification of Disease-10 criteria, whereas severity of depression was assessed using Hospital Anxiety and Depression Scale-depression (HADS-D) instrument. Outcome (depression-free) was measured at initial contact and also for each follow-up using HADS-D score. Chi-square and analysis of variance were used. Results: Fifty-one respondents out of 112 patients (46%) completed the study, and hence the sample size was 51 respondents. Females accounted for 65% (33) of the sample. Those who attained at least secondary level of education, and personal income as gave a P < 0.05 with regard to decrease HADS-D scores compare to when the study started, whereas the decrease HADS-D scores of sex and all age groups also gave a similar P < 0.05 as at the last follow-up of the study. Conclusion: Education status and personal income appear to affect the rate of response to antidepressant medications.
Keywords: Antidepressant medications, depression, sociodemographic factors
|How to cite this article:|
Edefo JW, Udezi WT. The effects of sociodemographic factors on depression management. N Niger J Clin Res 2016;5:59-63
| Introduction|| |
Depression is a clinical syndrome consisting of a core feature of low mood and/or inability to feel pleasure (anhedonia) together with numerous behavioral, emotional, cognitive, and biological features. ,
The International Classification of Disease-10 (ICD-10) identifies mild, moderate, and severe depression. Most typical symptoms of depression are depressed mood, loss of interest and enjoyment, and reduced energy, while other symptoms are reduced concentration and attention, reduced self-esteem and self-confidence, ideas of guilt and unworthiness, bleak and pessimistic views of the future, ideas or acts of self-harm or suicide, disturbed sleep, and diminished appetite. 
The symptoms listed above then define the degree of depression and management is based on the particular degree, namely, mild depression (four symptoms, with two most typical symptoms inclusive), moderate depression (5-6 symptoms, with at least two most typical symptoms inclusive), and severe depression (seven or more symptoms, with or without psychotic symptoms, with the three most typical symptoms inclusive). 
Although the precise cause of depression is not known, most likely, depression is caused by a combination of genetic, biological, environmental, and psychological factors. ,
Depressive disorders have a prevalence of 5% in the general population, , approximately, 10% in chronically ill medical outpatient, and an estimated 10% of people may become depressed during their lives (lifetime prevalence). 
The pathogenesis of depression is still unclear, but a few hypothesis has been postulated, this include amine hypothesis which suggests that decrease functional amine-dependent synaptic transmission by extension drugs (e.g., tricyclic antidepressants [TCAs], monoamine oxidase inhibitors [MOAIs], and selective serotonin reuptake inhibitors [SSRIs]) that increased amine function in appropriate synaptic areas would relieve depression. 
Antidepressant medications are the mainstay of drug management of depression. The classes of antidepressants include MAOIs, for example, phenelzine, selegiline, and tranylcypromine; TCAs such as amitriptyline, nortriptyline, and imipramine; SSRIs, for example, sertraline, citalopram, fluoxetine, and fluvoxamine; and serotonin-norepinephrine reuptake inhibitors which include venlafaxine and duloxetine.
Sociodemographic factors such as sex, age, income, education, and marital status which cut across the biological, environmental, and psychological may be predictors of depression outcome to antidepressant medications;  hence, the need to investigate the influence these factors on depression is of necessity.
The objective of the study
To explore the effect of sociodemographic factors on response rate to antidepressants therapy in depression management.
| Methods|| |
A prospective study design of 6 follow-ups per patient after the initial contact was employed. Follow-up was done every 4 weeks for up to the 24 th week per patient that completed the study.
The study was conducted at Federal Neuro Psychiatric Hospital, Uselu, Benin, Edo, which is a 280-bed tertiary hospital in Nigeria. The hospital serves the people living in the state and neighboring states which include Delta, Ondo, Anambra, Kogi, and Rivers state with a population of about 13,000,000. Staffs include consultant psychiatrists, residents' doctors, medical officers, pharmacists, intern pharmacists, pharmacy technicians, nurses, clinical psychologists, and other health professionals.
Research ethical approval
Ethical approval was granted by the Psychiatric Hospital Ethics Committee.
Inclusion and exclusion criteria
Outpatients above 18 years diagnosed for depression and managed with antidepressants were eligible. Patients were those who were newly diagnosed and managed of their condition commenced during the period of the study. Those that did not written informed consent were excluded from the study.
Patients who were prescribed antidepressants for indications other than depression (e.g., neuropathic pain) were excluded from the study. Those who were unable to fill the questionnaire due to their mental illness or any other conditions were excluded from the study.
All (census) those newly diagnosed of depression within the first 3 months of data collection period, who commenced antidepressant medication and who gave written informed consent participated in the study.
Method of data collection
Sociodemographic factors and costs were collected with the aid of a data collection sheet. Severity of depression was assessed by Hospital Anxiety and Depression Scale-depression (HADS-D) subscale instrument. ,
Outcome (depression-free) was measured at initial contact and also for each follow-up. ICD-10 criteria were used to diagnose depression. For each patient, the drug prescribed was noted. Other data collected include age, sex, and income per month. Outcome measure was based on depression free using the HADS-D subscale.
Data were collected through face-to-face contacts. Hawthorne effect was avoided as much as possible during data collection process. All outcome measures were self-completed, to avoid interviewer biased.
Data collected were entered, sorted, and descriptive analysis was done using Microsoft Excel. GraphPad Instat version 3.10 a statistics software published by GraphPad Software, Inc., a privately owned California corporation was used for inferential analysis. P < 0.05 was considered statistically significant.
Association between sex and severity of depression was determined using Chi-square, whereas the significant difference between mean HADS-D score ± standard deviation at the beginning of the study and as at when the study ended in the different sociodemographic factors considered were determined using one-way analysis of variance. ,
The outcome measure used was the number of respondents who were free from depression, that is, how many became normal individuals or free from depression during the course of the study. A score of below 8 on the HADS-D subscale was defined as depression free (normal individuals), a value of 8-10 as borderline individuals, and above 10 as abnormal patients (depressed patients). ,
| Results|| |
Respondents, 66% (33) were females, 64% (32) of the respondent got to secondary school level of education while about 24% (12) attained tertiary level of education, 90% (46) of the respondents had personal source of income, and 43% (22) were age 18-30 years.
There is no association between sex and severity of depression; HADS-D score revealed that 22% (11) were borderline (neither suffering from depression nor depression free), while 63% (32) were abnormal (suffering from depression) as at the time the study commenced [Table 1].
|Table 1: Mean Hospital Anxiety Depression Scale-depression sores±standard deviation at baseline for patients before treatment (n=51) |
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The response rate of the respondents to antidepressant medications of the different educational status at each month was the same; however, at 6 th month of the study, those that had at most primary school education had no difference in their HADS-D scores (depression free) compared to when they were recruited into the study [Table 2].
|Table 2: Mean Hospital Anxiety and Depression Scale-depression scores±standard deviation at different times of patients and educational status|
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The response rate on the basis of sex to males appears to respond better to antidepressants therapy from the 2 nd month of the study, this continued until the 4 th month, and thereafter there was no difference in response rate between the males and females; however, at the end of the study, both sexes showed a significant reduction in their HADS-D scores compared to when the study started [Table 3].
|Table 3: Mean Hospital and Anxiety Depression Scale-depression scores±standard deviation at different times of patients and sex |
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Patients response to antidepressant medications of the different age strata at each month were the same; however, at 6 th month of the study, the different age strata had differences in their HADS-D scores that is lower score compared to when they were recruited into the study [Table 4].
|Table 4: Mean Hospital and Anxiety Depression Scale - depression scores±standard deviation at different times for patients and age |
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Patients as regards to income, the response to antidepressant medications of the different income group at each month were only different in the second and 3 rd month, in addition, at the completion of the study, the income group that showed no significant difference in their HADS-D scores compare to when they were recruited into the study, were those that had no personal income [Table 5].
|Table 5: Mean Hospital Anxiety and Depression Scale - depression scores±standard deviation at different times of patients and monthly income |
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| Discussion|| |
About two-thirds of the respondents were females, as well as attained secondary school education; this can be attributed to the fact that females are more concern about their health and were willing to give consent to participate in the study.
Most of the respondents had personal source of income, while nearly half the number of the respondents were age 18-30 years, this showed that the incidence of epilepsy is higher in this age group compare to any other and the reason may be that this age group is almost in their prime hence takes their health seriously.
At the first contact assessment of depression of respondents using HADS-D subscale score, one-fifth of the respondents were neither suffering from depression nor depression free, about two-thirds were suffering from depression, while about one-sixth of the respondents were free from depression. All the respondents meet the ICD 10 criteria for depression at the first contact of the study.
The difference between ICD 10 and HADS-D may be due to differences in sensitivity of these instruments of diagnosing depression. There was no association between sex and severity of depression at the beginning of the study which means sex does not affect the severity of depression.
The mean HADS-D scores in respondents on the basis of educational status with at least secondary level of education showed a significantly lower value at the end of the study period compare to when the study began, this translates into significant positive response rate to antidepressants leading to respondents free from depression.
This finding as regards with the level of educational attainment affecting the response rate of antidepressant medications is consistent with a 9-month follow-up study were one of their important findings was that some baseline characteristics such as education was modest predictors of outcome in depression management.  In another study carried out posited that having more education gave a better positive response to acute pharmacotherapy among chronically depressed patients. 
The response rate with regard to sex, both sex appears to respond similar to antidepressants therapy. This was similar to a study done which showed that sex does not affect the response rate of antidepressant therapy. 
There was a positive response rate of antidepressant medication with different age groups which means age does not affect the response rate of antidepressants medications in depression management.
The response rate to antidepressants therapy for income earners resulted into a significant depression free month for patients at different income strata. Respondents without personal income showed no significant response rate at the beginning of the study compared to when the study began while those from income earner, more respondents were free from depression at the 6 th month compare to when the study started.
The result from income earners of patients in this setting agreed with secondary analysis of pooled data from the open-label phase clinical trials of nortriptyline hydrochloride or paroxetine combined with interpersonal psychotherapy which showed that respondents residing in the middle-income area were significantly more likely to respond to antidepressant treatment than those residing in the low-income area. 
| Conclusion|| |
Some demographic factors have found to be useful predictors of response to antidepressant therapy. Education status and having personal income appear to affect the rate of response to antidepressant medications with low educational status and no personal income showed no positive response rate while higher educational status and personal income showed positive response rate to antidepressant medications.
Financial support and sponsorship
Conflicts of interest
There are no conflicts of interest.
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[Table 1], [Table 2], [Table 3], [Table 4], [Table 5]