Keywords
Prenatal depression, Edinburgh Postnatal Depression Scale, Determinants, Case control
Prenatal depression, Edinburgh Postnatal Depression Scale, Determinants, Case control
To address the reviewers’ comments, in the methodology section, we have clarified that the study site was a county referral hospital. Besides, a description of study procedures, clarification on selection of cases and controls and information on validation of the data collection instruments for the setting have been provided. In the discussion, we have included the possible explanations for the lack of association between age, alcohol, substance abuse and prenatal depression. Since the study was facility-based, the possibility of selection bias has been added as a study limitation in the discussion. In the conclusion section, as recommended, we have indicated opportunities for future research to build on the present study.
See the authors' detailed response to the review by Abiodun Olugbenga Adewuya
See the authors' detailed response to the review by Linnet Ongeri
The prevalence of depression in women is about 20% with pregnancy increasing the susceptibility to depression1. Depression related to child bearing can develop either during pregnancy (prenatal depression), after birth (postnatal depression) or both periods (perinatal depression)2. Prenatal depression refers to a form of clinical depression which occurs during pregnancy and is characterized by chronic anxiety, insomnia, guilt, fatigue, irritability, forgetfulness, headaches and isolation3. The prevalence of prenatal depression in high income countries is between 7%–15% whereas the prevalence in low and middle income countries (LMICs) ranges between 19–25%4. In Africa, an 11.3% prevalence of prenatal depression has been reported5. Despite prenatal depression being a significant health problem, regrettably, it has received less attention than postpartum depression6–8. This is partly attributable to misconceptions about existing socio-cultural structures that could shield one from mental disturbance during this period6. Besides, more attention is paid to the physical health of the mother and fetus than on maternal mental health during pregnancy, with a propensity to dismiss emotional episodes as the result of hormonal imbalances. Thus, depression may persist silently during this period9.
Besides prenatal depression being a major determinant of post-natal depression, it is also a risk factor for adverse maternal and fetal outcomes such as premature births, preterm labor, low birth weight and poor infant feeding patterns10–12. Recent studies in Kenya have reported prenatal depression as a predictor for preterm delivery13 and underweight babies14. Moreover, prenatal depression is associated with impaired neurocognitive and socio-developmental disorders in the offspring such as poor motor and regulation skills, anti-social behavior and increased risk of depression and attention problems15 Additionally, higher health expenses, poor immunization rates and frequent hospitalization have also been reported in children who are born to depressed mothers16.
Predictors of prenatal depression can be categorized into three domains: social, psychological and biological risk factors. Social risk factors comprise low socio-economic status, lack of social support and stressors such as economic deprivation and unplanned pregnancy17. Women from a low socio-economic class are likely to have fewer financial resources which may be insufficient to meet the increasing financial demands of pregnancy and this may result to prenatal depression16. Likewise, women who lack social support are likely to have little emotional support from their spouses, family and friends and this can lead to social instability which subsequently leads to prenatal depression18. Gestational age, maternal age, genetic and hormonal susceptibility and obstetric complications are some of the biological risk factors for prenatal depression19. Women in their first trimester of pregnancy are likely to have higher depression rates than those in the third trimester and this is partly ascribable to the first trimester pregnancy symptoms like fatigue, nausea, food aversions and heartburn, which most women find difficult to cope with20. A history of stillbirth or miscarriage can be traumatic and may result in anxiety or depression18,21,22. The main psychological predictor of prenatal depression is a history of mental disorders23. Other predictors of prenatal depression in the Kenyan setting include adolescent pregnancy24 and mother’s HIV status25.
In Kenya, there are very few published research studies that have explored the factors associated with prenatal depression13. Given this paucity of research on prenatal depression in Kenya there is need to understand the predictors of prenatal depression with a view to informing the design of specific interventions and formulation of guidelines for the effective prevention, control and surveillance of prenatal depression particularly in high-risk regions in Kenya. Consequently, the objective of this study was to investigate the sociodemographic, lifestyle, obstetric and social network and family determinants of prenatal depression among women attending the antenatal clinic (ANC) at a referral facility in Mombasa County, Kenya.
A hospital-based case control study design was used to identify the determinants of prenatal depression. The choice of study design owes to its suitability in the investigation of rare outcomes that may be missed through random sampling. Although a population-based study would have been more optimal, a hospital-based design was selected due to the ease of recruitment of pregnant mothers (cases and controls) presenting to the antenatal clinic for care.
The study was conducted at the Coast Provincial General Hospital (CPGH) which is a county referral public facility located in Mombasa County, Kenya. The facility’s total catchment population is roughly four million people and includes the neighboring Coastal counties26. The antenatal clinic offers routine ANC services and the clinic visits are scheduled monthly with the average number of clinic visits per pregnant woman being four. The number of first-time antenatal visits per month is on average 140. Notably, prenatal depression is not screened for during ANC visits.
The study population comprised pregnant women ≥15 years attending routine ANC at CPGH during the data collection period between April and June 2019. All pregnant women who consented to participate were recruited to the study. Women who had already been diagnosed with depression prior to pregnancy or had concurrent chronic illnesses were excluded from the study.
Recruitment and interview of participants was carried out by two hospital-based research assistants (registered nurses) who had previously been trained on interviewing techniques. Upon obtaining informed consent from the subjects, the Edinburgh Postnatal Depression Scale (EPDS) (either the English or Kiswahili version depending on the individual’s preference)27,28 was administered via a face-to-face interview in a private room within the ANC clinic. The EPDS tool was completed just before provision of routine ANC services.
A case was a pregnant woman aged ≥15 years residing in the hospital’s catchment area who had been attending the ANC clinic at CPGH during the two-month study period and registered an EPDS score of ≥1329. All cases meeting this definition were prospectively recruited into the study until the required total was realized (see sample size determination).
Controls were pregnant women similarly defined as cases but with EPDS scores of <1327 presenting to the same ANC clinic for care. Owing to the comparably large number of controls, these were simple randomly sampled and frequency-matched to cases by day of presentation.
The appropriate sample size was estimated as per Kelsey et al.30 for case control studies:
n2 = rn1
Whereby:
n1 = number of cases and n2 = number of controls. p1 = proportion of cases with previous history of intimate partner violence (IPV) or domestic violence (primary exposure) and p2 = proportion of controls with previous history of IPV (set at 0.40)31. Of note, Zα/2 (1.96) is the value for a two-tailed 95% confidence level and Z1–β (-0.84) is the value for a statistical power of 80%. The odds ratio for the IPV-prenatal depression association was hypothesized to be 331. To enhance statistical power, a ratio of four controls per case was employed. Based on these estimates, a total sample size of 34 cases and 136 controls was derived.
Information on predictor variables was collected from the case and control participants using a semi-structured questionnaire (administered in a similar manner as the EPDS tool) (see Extended data)32 and included demographic characteristics, lifestyle, social network and family risk factors and obstetrical factors. The demographic predictors included age, level of education, occupation and marital status. Social network and family related predictors consisted of social support and domestic violence. Lifestyle factors comprised smoking, use of alcohol and substance abuse. Obstetric factors were unplanned pregnancy, gestational age, history of still birth, history of miscarriage/pregnancy loss and parity. Table 1 shows the method of assessment of the study variables. Figure 1 displays the relationship between the predictor variables and outcome.
Variable (type) | Method of assessment |
---|---|
Prenatal depression (nominal) | Denoted in binary form: Present or absent. This was assessed using the Edinburgh Postnatal Depression Scale which is a 10-item questionnaire which scores women’s feelings and experiences of the last one week on a likert scale. The recommended cut offs for the English and Swahili version is ≥13. The sensitivity and specificity of EPDS in the African setting has been shown to be 94% and 77% respectively27. The EPDS scale has shown to be the most reliable instrument used for screening of antenatal depression in resource constrained settings because of the reported specificity, sensitivity and reliability33. Furthermore, the EPDS has been validated for use in Kenya34. A score of ≥13 denoted presence of prenatal depression while a score of <13 denoted absence of prenatal depression |
Age (continuous) | Captured in years |
Level of education (ordinal) | The level of education attained by the pregnant women attending ANC. Categorized into three levels: 1= Primary school, 2= secondary school and 3=tertiary level |
Occupation (nominal) | Assessed in two levels: Employed or Unemployed |
Tobacco use (ordinal) | Through smoking or chewing and it was graded into 3 groups: Non user, rare user or regular user35 |
Alcohol intake (ordinal) | Graded into 3 categories: Non user, rare user or regular user35 |
Substance abuse (ordinal) | Cannabis, cocaine, heroin, valium, rohypnol, muguka, miraa, codeine and glue were assessed under substance abuse. Graded into 3 groups: Non user, rare user or regular user35 |
Current gestational age (continuous) | Abstracted from the ANC booklet based on the LMP. This was captured in weeks |
Parity (nominal) | Abstracted from the ANC booklet. This was captured as either primiparous or multiparous |
Unplanned pregnancy (nominal) | This was captured as either planned or unplanned |
Obstetric complications (nominal) | Comprised a history of either of the following: abortion, miscarriage, still birth, premature birth or fistula. They were assessed as either being present or absent. |
Social support (ordinal) | This was assessed using the English version of the Social Provisions Scale (SPS-10)36. The SPS-10 is a reliable and valid measure of social support with an overall Cronbach’s alpha of 0.9236 and it has been used to assess social support in LMICs as well as in pregnant women populations37. Captured as 0=Lack of social support, 1=Presence of social support |
Domestic violence (ordinal) | It was assessed through the English version of the Composite Abuse Scale (CASR-SF) which is a description of actions that women report as abusive by their spouses. The composite abuse scale has been validated in the assessment of IPV and is the recommended IPV assessment tool by Centers for Disease Control and Prevention38. It has been used in Kenyan studies and has demonstrated high validity with a Cronbach’s alpha of 0.91739. This was categorized as 0 = no lifetime experience of abuse and 1 = lifetime experience of abuse present40 |
Approval to conduct the study was obtained from the Kenyatta National Hospital-University of Nairobi (KNH-UON) Ethics and Research Committee (P787/11/2018). Written informed consent was secured from the participants prior to engaging in the study.
Following data collection, the questionnaires were manually checked for completeness and accuracy. Data were then double entered by two data entry clerks into an Excel Spreadsheet, after which the resulting datasets were compared and revisions made accordingly. Interviewer bias was minimized by training the research assistants on the standard operating procedures (SOPs) to ensure consistency in elicitation of information from the respondents. In a bid to minimize recall bias information such as the gestational age, the obstetric history and number of antenatal clinic visits was abstracted from the mother and child health booklet.
The Excel dataset was exported to Stata version 13.0 (Stata Corporation, College Station, Texas, USA) for analysis.
Descriptive statistics (medians, means, standard deviations and inter-quartile ranges) were used to summarize continuous variables. Proportions and percentages were generated for categorical variables. In the univariable analysis, the effect of each predictor on the odds of prenatal depression was assessed using logistic regression at a liberal P-value (P≤0.20)41. Since inclusion of age as a continuous variable was insignificant in the univariable analysis, it was categorized into three groups: 18–25 years, 26–29 years and 30–44 years and reassessed for significance as a categorical variable.
Variables that were found to be significant in the univariable analysis were offered to a multivariable model, where a backward step-wise approach was used to eliminate variables from the model at P>0.05. Notably, the non-significant variables were eliminated from the model if their exclusion from the model did not result in a greater than 30% change in the effects of the remaining variables41. Two-way interactions were fitted between the remaining variables in the final model and their significance assessed. A Hosmer-Lemeshow test was used to assess the goodness of fit of the logistic model, with a P-value of > 0.05 being suggestive of a good fit.
A total of 170 pregnant women (34 cases, 136 controls) were enrolled into the study.
A study flow chart illustrating the enrollment process is shown in Figure 2. Table 2 shows the descriptive statistics of the respondents.
The mean age of the respondents was 27.8 years (range: 18–44 years) with the mean age of cases being 27.0 years (range: 19–36 years) and that of controls being 28.0 years (range: 18–44 years). On the level of education, 44.1% (n=75) of the respondents had attained a tertiary level of education; this comprised 50.0% (n=17) of the cases and 42.7% (n=58) of the controls. Only 45.3% (n=77) of the respondents were employed, of which 26.5% (n=9) were cases and 50% (n=68) were controls.
Respondents who reported to have consumed alcohol, tobacco or abused substances during the pregnancy period constituted 14.7% (n=25) of the population. Amongst these 29.4% (n=10) were cases and 11% (n=15) were controls.
A fifth (20%, n=34) of the respondents reported that the current pregnancy was unplanned. Of these, 38.2% (n=13) were cases while 15.4% (n=21) were controls. Approximately 19% (18.8%, n=32) of the participants reported to have experienced obstetric complications in previous pregnancies. Of these, 26.5% (n=9) were cases and 16.9% (n=23) were controls.
Majority of the participants had received social support (88.2%, n=150). In particular, 61.8% (n=21) of the cases reported to have had social support compared to 94.9% (n=129) of the controls. The proportion of women who experienced domestic violence was 27.6% (n=47), with this proportion being higher among cases at 64.7% (n=22) than in controls at 18.4% (n=25).
Of the factors assessed, only age, marital status, occupation, alcohol and substance abuse, unplanned pregnancy, gestational age, social support and domestic violence were associated with prenatal depression at P≤0.2. (Table 3). These variables were subsequently included in the multivariable model. In the multivariable analysis, only marital status, occupation, social support and domestic violence were shown to be significant predictors of prenatal depression at 5% significance level (Table 4). Exclusion of the non-significant variables from the model did not result in ≥30% change in the effects of the remaining variables.
Variable | Value | Odds ratio | 95% CI | P-Value |
---|---|---|---|---|
Age* | 18–25 | Ref | 0.045 | |
26–29 | 2.2 | 0.9–5.3 | ||
30–44 | 0.7 | 0.3–1.9 | ||
Education | Primary | Ref | 0.335 | |
Secondary | 0.5 | 0.2–1.5 | ||
Tertiary | 0.9 | 0.3–2.3 | ||
Marital status* | Married | Ref | <0.001 | |
Single | 6.7 | 2.5–18.1 | ||
Occupation* | Employed | Ref | 0.012 | |
Unemployed | 1.7 | 1.1–2.5 | ||
Alcohol and drug use* | Non-user | Ref | 0.012 | |
User | 3.4 | 1.3–8.4 | ||
Gestational age* | 3rd trimester | Ref | 0.124 | |
2nd trimester | 1.8 | 0.8–3.9 | ||
Parity | Primiparous | Ref | 0.875 | |
Multiparous | 1.1 | 0.5–2.3 | ||
Unplanned pregnancy* | No | Ref | 0.004 | |
Yes | 3.4 | 1.5–7.8 | ||
Obstetric complications | No | Ref | 0.228 | |
Yes | 1.4 | 0.8–2.3 | ||
Social support* | No | Ref | <0.001 | |
Yes | 0.08 | 0.03–0.2 | ||
Domestic violence* | No | Ref | <0.001 | |
Yes | 8.1 | 3.5–18.6 |
Compared to participants who were married, those who were single had 17.1 times the odds (adjusted odds ratio (aOR)=17.1; 95% confidence interval (CI): 4.0-73.0) of prenatal depression controlling for their occupation, domestic violence and social support status. Unemployed respondents had 2.4 times the odds of prenatal depression (aOR=2.4; 95% CI: 1.4-4.2) as employed participants holding their marital status, domestic violence experience and social support constant. Participants who experienced domestic violence had 18.3 times the odds of prenatal depression (aOR=18.3; 95% CI: 5.7-58.7) compared to those who did not experience domestic violence regardless of their marital status, occupation and social support level. Respondents who had social support had one-fifth the odds of prenatal depression (aOR=0.2; 95% CI: 0.05-0.8) in comparison to those who did not have social support controlling for their marital status, occupation and domestic violence experience.
The model had a good fit (P = 0.403).
Marital status was shown to be a significant predictor of prenatal depression among women in the study with single women having higher odds of prenatal depression compared to those who were married. This finding is corroborated by other studies21,42. Being single as a result of a break up or abandonment by a partner can result in emotional problems and lack of social support from the male partners and this could lead to depression. Moreover, single parenting is stigmatized in the African culture and this may predispose one to antenatal depression43.
This study found that unemployed women had higher odds of prenatal depression compared to their employed counterparts. This finding is similar to that reported by a study in Italy44 which found that participants who were unemployed had 2.17 times the odds of prenatal depression compared to those who were employed. Another study conducted among Japanese women revealed that employment is protective against prenatal depression45. Pregnant women who are unemployed have fewer financial resources which may be insufficient to meet the increasing demands of pregnancy and this may predispose to prenatal depression.
Domestic violence was strongly associated with prenatal depression in this study. These findings are consistent with those from other studies, which described gender-based violence as an important predictor of prenatal depression with women who experience psychological, physical and sexual violence being prone to antenatal depression46–48. Domestic violence may cause physical injury with attendant emotional and psychological trauma that can lead to depression49.
Social support was protective against prenatal depression in this study. These findings support the results of other studies18,43,50–52. Social support from a spouse, friends or relatives provides psychosocial resources during pregnancy and these act as a cushion against difficulties that may be experienced during pregnancy hence can protect one from antenatal depression. In contrast, women who lack social support are likely to have little emotional support from their spouses, family and friends bringing about social instability which can heighten the risk of prenatal depression53,54.
Age did not significantly influence the likelihood of prenatal depression in this study. This could partly be explained by the presence of the stronger risk factors (marital status, occupation, domestic violence and social support) for prenatal depression than age in the multivariable model. However, other studies have revealed that age is a significant predictor of prenatal depression owing to the fact that young pregnant women are likely to be financially unstable and may not be socially and psychologically prepared to cope with pregnancy demands and this may predispose them to depression55. Contrarily, some studies have demonstrated that older women are at a higher risk of developing prenatal depression as ageing increases the possibility of experiencing difficulties in conceiving and anxiety of experiencing obstetric complications. Besides, there is a high likelihood of experiencing stigma when you conceive later in life56,57.
Use of alcohol and abuse of drugs did not significantly predict a participant’s probability of developing prenatal depression taking into account the effect of other variables. This finding could possibly be due to the fact that, per the causal diagram, the relationship between substance abuse and prenatal depression is partly mediated through domestic violence and social support so that when they are adjusted for in the presence of substance abuse, the relationship is substantially weakened. The findings of this study concur with the results of a study conducted among African American women58. On the contrary, other studies have reported a significant relationship between alcohol and drug abuse and prenatal depression42,59,60. Alcohol being a depressant may inhibit neurotransmitters that regulate mood such as serotonin and norepinephrine, and this can lead to depression61.
After accounting for other variables, unplanned pregnancy was not found to be significantly related to developing prenatal depression in this study. This is partly ascribable to the fact that although an unplanned pregnancy might be unwanted at first, as the pregnancy progresses the shock associated with the undesired occurrence decreases and it becomes increasingly accepted, hence reducing the symptoms of depression62. Other studies have reported a significant association between unplanned pregnancy and prenatal depression which is related to the fact that unplanned pregnancy is associated with lack of preparedness to deal with the financial and psychological demands of pregnancy46,63,64.
Gestational age was not found to be associated with prenatal depression after controlling for other variables. This finding is similar to another study that was conducted in KwaZulu-Natal65. Nonetheless, other studies have demonstrated that women who are in the second or third trimester are less likely to be depressed antenatally compared to women in the first trimester owing to the fact that during the first trimester some women find it difficult to cope with pregnancy symptoms like nausea and food aversions and this can lead to depression9,42,66. The results from this study are generalizable to populations of pregnant women presenting for ANC services in similar LMIC settings.
A couple of limitations are present in this study. There was likely to be differential recall of past exposures between cases and controls with cases having better recall than controls. Moreover, cases were more likely to over-report their exposures and this could bias the effect estimates away from unity. The case definition of prenatal depression only relied on EPDS, which is a screening tool; this could have been supplemented by a clinical examination of the participants to improve on detection of prenatal depression. Moreover, considering the facility-based nature of the study, the results are likely to suffer selection bias since it is probable that depressed women would be less inclined to present themselves for antenatal care. This is likely to have biased the effect estimates towards unity.
The present study showed that marital status, occupation, domestic violence and lack of social support were the predictors of prenatal depression in this setting. To address the burden of prenatal depression in the country, we advocate for the inclusion of screening for prenatal depression as an essential component of the antenatal care package. We recommend that future research focuses on evaluating specific interventions to address the identified predictors of prenatal depression.
Harvard Dataverse: prenatal depression CPGH. https://doi.org/10.7910/DVN/QIFMOT.
This project contains the following underlying data:
Harvard Dataverse: prenatal depression CPGH. https://doi.org/10.7910/DVN/QIFMOT.
This project contains the following extended data:
Prenatal depression_questionnaire.pdf (questionnaire used in this study).
prenatal_depression_code.do (STATA commands file for determinants of prenatal depression evaluation).
Data are available under the terms of the Creative Commons Zero "No rights reserved" data waiver (CC0 1.0 Public domain dedication).
The authors are grateful to the study participants and staff members of the Coast Provincial General Hospital antenatal clinic for their support throughout the data collection process and their contribution to the success of this study. We also wish to express our appreciation to the Coast Provincial General Hospital administration for authorizing use of the facility for the study.
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Competing Interests: No competing interests were disclosed.
Reviewer Expertise: I am a psychiatrist and mental health researcher. I have published papers on perinatal depression
Is the work clearly and accurately presented and does it cite the current literature?
Partly
Is the study design appropriate and is the work technically sound?
Partly
Are sufficient details of methods and analysis provided to allow replication by others?
Partly
If applicable, is the statistical analysis and its interpretation appropriate?
Partly
Are all the source data underlying the results available to ensure full reproducibility?
Partly
Are the conclusions drawn adequately supported by the results?
Yes
References
1. Green E, Tuli H, Kwobah E, Menya D, et al.: Developing and validating a perinatal depression screening tool in Kenya blending Western criteria with local idioms: A mixed methods study. Journal of Affective Disorders. 2018; 228: 49-59 Publisher Full TextCompeting Interests: No competing interests were disclosed.
Reviewer Expertise: Public Mental Health
Is the work clearly and accurately presented and does it cite the current literature?
Yes
Is the study design appropriate and is the work technically sound?
Yes
Are sufficient details of methods and analysis provided to allow replication by others?
Partly
If applicable, is the statistical analysis and its interpretation appropriate?
Yes
Are all the source data underlying the results available to ensure full reproducibility?
Yes
Are the conclusions drawn adequately supported by the results?
No
Competing Interests: No competing interests were disclosed.
Reviewer Expertise: I am a psychiatrist and mental health researcher. I have published papers on perinatal depression
Alongside their report, reviewers assign a status to the article:
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Version 1 23 Jan 20 |
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