Depression is a mood disorder which is characterized by prolonged sadness and marked loss of interest in daily activities as core symptoms lasting for one week or more. Other symptoms are numbness, feeling inadequate and worthless, feeling irritable and resentful, insomnia, appetite changes, decreased energy, lack of concentration and poor memory, and thoughts of committing suicide or abortion [
Women have a lifetime risk of about 1 in 8, and it is most prevalent during their reproductive years [
Pregnancy and depression affect each other. Pregnancy is a major psychological, as well as, physiological event. With an excess of chronic life stressors, women may find themselves unable to cope with the additional demands of pregnancy. Many women, particularly those living in poverty or already with dependent children, may view pregnancy with negative feelings. Issues or memories surrounding poor parenting or abuse women have suffered may reassert themselves and cause distress. Relationships are often under pressure because domestic violence increases during pregnancy [
Pregnancy-related sex steroids increase activation of hypothalamic-pituitary-adrenal (HPA) axis which is associated with depression [
The prevalence of prenatal depression is estimated to be 10–15% in developed countries and 19–25% in economically poorer countries [
Depression is one of the most prevalent psychiatric conditions in the community. However, it is neither well recognized nor adequately treated in clinical practice [
Antenatal depression has been implicated in nutritional deprivation and poor maternal weight gain during pregnancy. These are associated with intrauterine growth retardation (IUGR) and low neonatal birthweight [
A study has found that there is an association between antenatal depression and labour complications such as prolonged labour, peripartum complications, postpartum complications, and nonvaginal delivery [
In addition, some depressed pregnant women engage in smoking of cigarettes and drinking alcohol. This dangerous habit affects the development of the fetus and can cause miscarriages, intrauterine deaths, and intrauterine growth restrictions [
High prevalence of antenatal depression may affect the millennium development goals which are decreasing child mortality (MDG 4) and improving maternal health (MDG 5), hence the need to explore the prevalence and risk factors of antenatal depression in order to provide evidence on the burden and for planning intervention.
Although researches have been carried out on antenatal depression worldwide, there is paucity of work done on it in Nigeria and Abeokuta in particular. A research which was carried out in Nigeria [
Another important reason for conducting this study was to contribute to the body of knowledge of antenatal depression and identify the most prevalent predictors of antenatal depression among pregnant women since this condition is neither well recognized, thoroughly studied, nor properly treated clinically [
Therefore, this study aimed to determine the prevalence of antenatal depression and associated risk factors among pregnant women in Abeokuta North Local Government Area (LGA), Ogun State. In addition, health seeking behaviour for antenatal depression among the women was explored.
Abeokuta North LGA is a local Government Area in Ogun State of Nigeria. It has a population of 201,329 and the population of child bearing women (15–49 years) is 51,203 at the 2006 census [
The people are predominantly farmers, most of whom engage in cultivation of arable crop, while some engage in livestock and fishing. In recent times, the people of the area are involved in quarry business, artisan works, and handicrafts such as tie and dye making and pottery [
This was a cross-sectional study.
This included all pregnant women attending Antenatal Clinics in Abeokuta North LGA. Any client registering for ANC service on the day of data collection at any facility was included. Pregnant women with physical disabilities such as deafness and dumbness as well as those with a history of or ongoing mental illness/retardation were excluded.
The study sample size of 276 was calculated using sample size formula for cross-sectional study with a prevalence of 8.7% from a study in Nigeria by Adewuya et al., 2007, precision of 5%, and standard normal deviate of 1.96 at 95% confidence intervals. A nonresponse rate of 15% and design effect of two were considered.
This study was approved by the Ogun State Ministry of Health Ethical Board in October 2015. Participants had the right to accept or decline request to participate. Written informed consent was obtained from the participants and their confidentiality was preserved. They were assured of getting the benefits of valuable information about their health, appropriate health advice on how to manage their conditions, and final feedback at the end of the project.
Multistage cluster sampling technique was used.
In Abeokuta North Local Government Area, there were about 22 health facilities that offered antenatal care (ANC) services.
Primary health facilities: they were divided into public and private. With regard to public health facilities, there were six community health centers, while, for the private, there were nine private maternity clinics. Secondary health facilities: there were no secondary public health facilities (general or state hospitals) in Abeokuta North LGA. However, there were six private hospitals that offered ANC services. Tertiary health facilities: there are two tertiary health institutions in Abeokuta North LGA, namely, Neuropsychiatric Hospital, Aro, and Olabisi Onabanjo University Teaching Hospital (OOUTH), Saje Annex. Of these two, only OOUTH Saje Annex offered ANC services.
Using equal allocation random sampling, the sample size of 314 was shared among the three tiers of health facilities, giving 104 for each tier.
At the primary level, using proportionate allocation ratio of 2 : 3 for primary health centers to maternity clinics, two primary health centers were randomly selected from the six health centers and three maternity clinics were selected randomly from the nine private maternity clinics.
At the secondary level, only private hospitals were sampled since there was no functional public (government) hospital. Two out of the six private hospitals offering ANC services were randomly selected.
At the tertiary level, only OOUTH Saje Annex offered ANC services. So, it was selected.
At the secondary level, there were two private hospitals. The sample size for each was 52.
At the tertiary level, 104 willing participants were surveyed from the only institution offering antenatal care.
A questionnaire was developed by the investigator borrowing questions from past studies instruments and knowledge of antenatal depression. In addition, the Edinburgh Postnatal Depression Scale was adopted.
The questionnaire had three sections. The first section focused on sociodemographic characteristics such as age, marital status, ethnicity, occupation, level of education, family size, and social as well as obstetrics history. The second section was on risk factors of depression. In addition the Edinburgh Postnatal Depression Scale (EPDS), a screening instrument to detect depressive symptoms, is used by Epidemiologists and researchers as a substitute for clinical diagnosis of Major Depressive Disorder (MDD). The EPDS is a ten-item self-report scale which was designed in 1987 and was originally meant for postnatal depression. It has since been validated for use in both pregnant and nonpregnant women. The maximum value for EPDS is 30 while the minimum is 0 [
Data collected were entered and stored in a password-protected computer. Statistical Package for Social Science SPSS version 16.0 was used for data entry and analysis. Data cleaning was done prior to analysis. Descriptive statistics such as percentages, means, and standard deviation and range were used to summarize the data. Student’s
The wealth scores were calculated from respondents’ household possession using principal component analysis and grouped into five (quintiles) to give the wealth index. The rich and the very rich had positive wealth score, the average had zero wealth score, and the poor and the very poor had negative wealth score.
With regard to social support, five questions were asked about people in each respondent’s life who provided her with help or support. Then, using Sarason et al.’s [
Table
Frequency distribution of the sociodemographic characteristics of the respondents.
Characteristics | Frequency ( | Percentage (%) |
---|---|---|
| ||
15–20 yrs (young) | 34 | 10.9 |
21–35 yrs | 255 | 82.0 |
36–49 yrs | 22 | 7.1 |
| ||
| ||
Yoruba | 308 | 98.1 |
Others | 6 | 1.9 |
| ||
| ||
Single | 18 | 5.7 |
Married | 292 | 93.0 |
Others (separated or divorced) | 4 | 1.3 |
| ||
| ||
No formal education | 7 | 2.2 |
Primary | 75 | 24.0 |
Secondary | 158 | 50.6 |
Tertiary | 72 | 23.1 |
| ||
| ||
Monogamous | 230 | 78.5 |
Polygamous | 61 | 20.8 |
Others | 2 | 0.7 |
| ||
| ||
Small (1–4 persons) | 204 | 68.9 |
Average (5 persons) | 41 | 13.9 |
Large (6 persons and above) | 51 | 17.2 |
| ||
| ||
Civil servants | 6 | 1.9 |
Unemployed | 10 | 3.2 |
Students | 13 | 4.2 |
Professional | 34 | 10.9 |
Artisans | 74 | 23.8 |
Traders | 174 | 55.9 |
| ||
| ||
Very poor | 48 | 15.3 |
Poor | 131 | 41.7 |
Average | 70 | 22.3 |
Rich | 55 | 17.5 |
Very rich | 10 | 3.2 |
| ||
| ||
Yes | 1 | 0.3 |
No | 297 | 99.7 |
| ||
| ||
Yes | 17 | 5.8 |
No | 277 | 94.2 |
| ||
| ||
Beer | 5 | 29.4 |
Wine | 6 | 35.3 |
Spirit/liquor | 6 | 35.3 |
| ||
| ||
For pleasure | 15 | 88.2 |
Medicinal | 2 | 11.8 |
| ||
| ||
Low social support (SSQN < 1) | 29 | 9.2 |
Average social support (SSQN = 1) | 216 | 68.8 |
High social support (SSQN > 1) | 69 | 22.0 |
| ||
| ||
Rape | 6 | 1.9 |
Intimidation/threat | 16 | 5.1 |
Inadequate financial support/financial deprivation | 16 | 5.1 |
Physical assault | 18 | 5.7 |
None | 258 | 82.2 |
| ||
| ||
Pleasant (enjoyable) | 239 | 76.1 |
Unpleasant (gloomy) | 17 | 5.4 |
I do not know | 58 | 18.5 |
Table
Frequency distribution of respondents by history of index pregnancy and past gynaecological/obstetric history among respondents.
Variables | Frequency ( | Percentage (%) |
---|---|---|
| ||
First trimester (1–3 months) | 51 | 16.3 |
Second trimester (4–6 months) | 92 | 29.4 |
Third trimester (7–9 months) | 170 | 54.3 |
| ||
| ||
Yes | 236 | 75.4 |
No | 77 | 24.6 |
| ||
| ||
Hypertension | 2 | 0.7 |
Diabetes | 1 | 0.3 |
HIV | 5 | 1.6 |
Others | 4 | 1.3 |
No coexisting condition | 293 | 96.1 |
| ||
| ||
Primigravida | 71 | 23.0 |
Multigravida | 238 | 77.0 |
| ||
| ||
Nullipara | 91 | 29.6 |
Primipara | 93 | 30.3 |
Multipara | 123 | 40.1 |
| ||
| ||
None | 218 | 71.9 |
One or more | 85 | 28.1 |
| ||
| ||
Male | 172 | 47.9 |
Female | 187 | 52.1 |
| ||
| ||
Caesarian section | 10 | 2.8 |
Vaginal delivery | 349 | 97.2 |
| ||
| ||
Low birth weight (<2.5 kg) | 6 | 1.7 |
Normal weight (2.5–4.0 kg) | 351 | 97.8 |
High birth weight (>4.0 kg) | 2 | 0.6 |
| ||
| ||
Yes | 359 | 100.0 |
No | 0 | 0.0 |
The results of screening carried out among participants using Edinburgh Postnatal Depression Scale (EPDS) showed that seventy-seven (24.5%) scored 12 and above which was suggestive of depression while the rest, 237 (75.5%), scored below 12. The overall prevalence of antenatal depression was 24.5%. Prevalence of antenatal depression in first, second, and third trimesters was 27.5%, 25%, and 23.5%, respectively.
Table
Associations between sociodemographic variables and antenatal depression.
Characteristics | Depressed | Nondepressed | Total (%) | | |
---|---|---|---|---|---|
| |||||
Primary | 28 (26.4) | 78 (73.6) | 106 (100) | ||
Secondary | 13 (12.5) | 91 (87.5) | 104 (100) | 14.051 | 0.001 |
Tertiary | 36 (34.6) | 68 (65.4) | 104 (100) | ||
| |||||
| |||||
Public health facilities | 55 (35.3) | 101 (64.7) | 156 (100) | 19.300 | 0.000 |
Private health facilities | 22 (13.9) | 136 (86.1) | 158 (100) | ||
| |||||
| |||||
15–20 years (young) | 15 (44.1) | 19 (55.9) | 34 (100) | ||
21–35 years | 58 (22.7) | 197 (77.3) | 255 (100) | 8.917 | 0.012 |
36–49 years (elderly) | 3 (13.6) | 19 (86.4) | 22 (100) | ||
| |||||
| |||||
Single | 9 (50) | 9 (50) | 18 (100) | 6.697 | 0.010 |
Married/others | 68 (23) | 228 (77) | 296 (100) | ||
| |||||
| |||||
No formal education | 5 (71.4) | 2 (28.6) | 7 (100) | ||
Primary | 17 (22.7) | 58 (77.3) | 75 (100) | 9.592 | 0.022 |
Secondary | 41 (25.9) | 117 (74.1) | 158 (100) | ||
Tertiary | 14 (19.4) | 58 (80.6) | 72 (100) | ||
| |||||
| |||||
Professionals | 6 (17.6) | 28 (82.4) | 34 (100) | ||
Civil servants | 1 (16.7) | 5 (83.3) | 6 (100) | ||
Artisans | 17 (23) | 57 (77) | 74 (100) | 3.837 | 0.429 |
Traders | 44 (25.3) | 130 (74.7) | 174 (100) | ||
Students/unemployed | 9 (39.1) | 14 (60.9) | 23 (100) | ||
| |||||
| |||||
Monogamy | 53 (23) | 177 (77) | 230 (100) | 0.019 | 0.891 |
Polygamy/others | 14 (22.2) | 49 (77.8) | 63 (100) | ||
| |||||
| |||||
Small family size (1–4 persons) | 49 (24) | 155 (76) | 204 (100) | ||
Average family size (5 persons) | 4 (9.8) | 37 (90.2) | 41 (100) | 7.047 | 0.029 |
Large family size (≥6 persons) | 17 (33.3) | 34 (66.7) | 51 (100) | ||
| |||||
| |||||
Very poor | 14 (29.2) | 34 (70.8) | 48 (100) | ||
Poor | 34 (26) | 97 (74) | 131 (100) | ||
Average | 16 (22.9) | 54 (77.1) | 70 (100) | 1.528 | 0.822 |
Rich | 11 (20) | 44 (80) | 55 (100) | ||
Very rich | 2 (20) | 8 (80) | 10 (100) | ||
| |||||
| |||||
Yes | 9 (52.9) | 8 (47.1) | 17 (100) | 8.441 | 0.004 |
No | 61 (22) | 216 (780) | 277 (100) | ||
| |||||
| |||||
Low social support | 10 (34.5) | 19 (65.5) | 29 (100) | ||
Average social support | 53 (24.5) | 163 (75.5) | 216 (100) | 2.222 | 0.329 |
High social support | 14 (20.3) | 55 (79.7) | 69 (100) | ||
| |||||
| |||||
Rape | 3 (50) | 3 (50) | 6 (100) | ||
Physical assault | 9 (50) | 9 (50) | 18 (100) | ||
Intimidation/threat | 8 (50) | 8 (50) | 16 (100) | 18.636 | 0.001 |
Financial deprivation/poor | 6 (37.5) | 10 (62.5) | 16 (100) | ||
Financial support | |||||
None | 51 (19.8) | 207 (80.2) | 258 (100) | ||
| |||||
| |||||
Pleasant | 58 (24.3) | 181 (75.7) | 239 (100) | 2.395 | 0.122 |
Unpleasant | 7 (41.2) | 10 (58.8) | 17 (100) |
Table
Associations between obstetric/gynaecological variables and antenatal depression.
Characteristics | Depressed | Nondepressed | Total (%) | | |
---|---|---|---|---|---|
| |||||
First trimester (1–3 months) | 14 (27.5) | 37 (72.5) | 51 (100) | ||
Second trimester (4–6 months) | 23 (25) | 69 (75) | 92 (100) | 0.336 | 0.845 |
Third trimester (7–9 months) | 40 (23.5) | 170 (76.5) | 170 (100) | ||
| |||||
| |||||
Yes | 50 (21.2) | 186 (78.8) | 236 (100) | 6.029 | 0.014 |
No | 27 (35.1) | 50 (64.9) | 77 (100) | ||
| |||||
| |||||
Present | 6 (50) | 6 (50) | 12 (100) | 4.503 | 0.034 |
Absent | 68 (23.2) | 225 (76.8) | 293 (100) | ||
| |||||
| |||||
Primigravida | 18 (25.5) | 53 (74.5) | 71 (100) | 0.059 | 0.809 |
Multigravida | 57 (23.9) | 181 (76.1) | 238 (100) | ||
| |||||
| |||||
Nullipara | 18 (19.8) | 73 (80.2) | 91 (100) | ||
Primipara | 27 (29) | 66 (71) | 93 (100) | 2.136 | 0.344 |
Multipara | 31 (24.2) | 92 (75.8) | 123 (100) | ||
| |||||
| |||||
None | 56 (25.7) | 162 (74.3) | 218 (100) | 0.365 | 0.546 |
One or more | 19 (22.4) | 66 (77.6) | 85 (100) | ||
| |||||
| |||||
Yes | 5 (55.6) | 4 (44.4) | 9 (100) | 4.589 | 0.032 |
No | 44 (23.8) | 141 (76.2) | 185 (100) |
When the factors found significantly associated with antenatal depression were put in logistic regression model, gender based violence (AOR = 4.3, 95% CI: 2.1–8.9), attending public health facilities (AOR = 5.0, 95% CI: 2.5–9.9), and drinking alcohol in pregnancy (AOR = 5.1, 95% CI: 1.7–14.9) were predictors of antenatal depression (Table
Results of multiple regression for predictors of antenatal depression.
Variables | Unadjusted OR | 95% CI | Adjusted OR | 95% CI |
---|---|---|---|---|
| ||||
15–20 years (ref) | 1.00 | |||
21–35 years | 2.68 | 1.28–5.61 | ||
36–49 years | 5.00 | 1.24–20.14 | ||
| ||||
| ||||
No formal education (ref) | 1.00 | |||
Primary | 8.53 | 1.52–47.95 | ||
Secondary | 7.13 | 1.33–38.20 | ||
Tertiary | 10.36 | 1.82–59.04 | ||
| ||||
| ||||
Single (ref) | 1.00 | |||
Married/others | 3.42 | 1.31–8.98 | ||
| ||||
| ||||
Small family size (1–4 persons) | 1.58 | 0.81–3.08 | ||
Average family size (5 persons) | 4.63 | 1.42–15.12 | ||
Large family size (≥6 persons) (ref) | 1.00 | |||
| ||||
| ||||
Public health facilities (ref) | 1.00 | |||
Private health facilities | 3.37 | 1.93–5.88 | 5.00 | 2.52–9.89 |
| ||||
| ||||
Yes (ref) | 1.00 | |||
No | 3.98 | 1.48–10.76 | 5.05 | 1.71–14.94 |
| ||||
| ||||
Present (ref) | 1.00 | |||
Absent | 3.90 | 2.10–7.24 | 4.31 | 2.09–8.88 |
| ||||
| ||||
Yes | 2.01 | 1.14–3.53 | ||
No (ref) | 1.00 | |||
| ||||
| ||||
Present (ref) | 1.00 | |||
Absent | 3.31 | 1.03–10.59 | ||
| ||||
| ||||
Yes (ref) | 1.00 | |||
No | 4.01 | 1.03–15.57 |
Figures
People respondents consulted when they were sad or lost interest in their routine activities (
Forms of treatment respondents sought when they were sad or lost interest in routine activities for over one week (
People who informed respondents’ decisions to get treated (
In this study, the prevalence of antenatal depression was 24.5%. This supports the finding of National Institute of Clinical Excellence which found prevalence of antenatal depression in developing countries to range from 19 to 25% [
In this study, the prevalence of antenatal depression in first, second, and third trimesters was 27.5%, 25.0%, and 23.5%, respectively. The prevalence of antenatal depression peaked in the first trimester and then gradually decreased across the second and third trimesters, albeit all trimesters having similar rates. Similar finding was observed by Gavin et al. who reported that prevalence of antenatal depression appears to peak in the first trimester [
The first-trimester prevalence of antenatal depression in this study corroborated the finding of a study with 357 pregnant women in Hong Kong in which antenatal depression prevalence was 22.1% [
Furthermore, the prevalence of AD in the third trimester, though lower than it was in the first and second trimesters, is still high at 23.5%. This is supported by a similar finding observed in a cross-sectional study carried out with 292 Chinese people where prevalence of AD in the third trimester was 28.5% [
Due to high prevalence of AD across the three trimesters, screening of pregnant women at each trimester should be established. This implies that a pregnant woman should be screened at least thrice for depression before childbirth, with one screening in each trimester. Education of risks associated with untreated antenatal depression should be initiated at various health facilities.
In this study, about ten risk factors were determined, out of which, three were identified as predictors of antenatal depression. The risk factors identified were attending antenatal care in public facilities, gender based abuse, drinking of alcohol in pregnancy, young age, presence of coexisting medical condition, history of previous caesarian section, unplanned pregnancy, single marital status, lack of education, and large family size.
In this study, attending a public health facility for antenatal care is a risk factor and predictor of antenatal depression. Though participants were not asked if the quality of service given in the public facilities affected them positively or negatively, some researchers in their studies identified possible reasons for public health facility being a risk factor. According to Mannava et al., who explored attitude and behaviour of health care workers towards their pregnant clients in Africa and Asia using secondary data from five electronic databases from January 1990 to December 2014, poor health care services were reported rendered in public health facilities. These poor services were long hours of waiting to see doctors or nurses due to high workload, absenteeism or unavailability of providers, verbal abuse, rudeness such as ignoring or ridiculing clients, neglect, authoritarian attitude, and frightening and unfriendly attitude of staff towards their pregnant clients [
Young age (15–20 years) was identified as a risk factor of AD in this study. Young age as a risk factor was also identified in some studies [
Premarital pregnancy was also identified as a risk factor of antenatal depression in this study and this may also be related to the association between AD and young age. Prevalence of AD among pregnant single ladies was 50%. A study in USA observed a similar finding [
Another risk factor identified in this study was unplanned pregnancy. In this study, prevalence of AD among pregnant women with unplanned pregnancy was 35.1%. Unplanned pregnancy has been reported in several studies as a risk factor of antenatal depression [
Furthermore, lack of education was identified as a risk factor of AD in this study. Lack of education of woman as a risk factor was also identified in another study [
In this study, the presence of a medical condition in pregnancy was a risk factor for AD. Some of these conditions were chronic illnesses such as HIV, hypertension, and diabetes mellitus. This is similar to findings observed in some studies in KwaZulu Natal, South Africa, and Rio de Janeiro, Brazil [
Another important risk factor and predictor of antenatal depression in this study was gender based abuse. This is supported by a similar finding in a study in California, Los Angeles [
Intake of alcohol in pregnancy was identified as a risk factor and predictor of antenatal depression in this study. Prevalence of alcohol intake in pregnancy was 5.8% in the study. This is well within a prevalence range of 1.9% and 11% observed in a study in Lagos, Nigeria [
Going further, history of previous caesarian section was found to be a risk factor of AD. This is supported by a finding observed in a study in Navi Mumbai, India [
Another risk factor identified in this study is large family size (≥6 persons). This is similar to an inference made from another study on antenatal depression [
The health seeking behaviour for antenatal depression among women with AD was assessed and important inferences were drawn. Most participants reported consulting their husbands/lovers about symptoms of depression (68.9%), followed by those who reported consulting their doctors (12.2%), family members (10.8%), and friends (5.4%). This is supported by similar findings observed in Ohio, USA, in a study which reported that more depressed pregnant women consulted their family (especially their husbands and mothers) and friends about symptoms of depression than they consulted health care professionals [
On treatment preferences for depression, some reported going to church for prayers (52%) and some reported going to the hospital to get treated (41.3%). Only three (4%) reported self-medication. Contrary finding was reported in Ohio, USA, by Henshaw who reported that most depressed women sought treatment in hospitals, followed by, in a distant second position, self-treatment at home, and seeking help in place of worship came at a very distant third position [
Another limitation is that it was not possible to determine causal relationships between depression and risk factors but only to determine associations. This is due to the fact that the research was a cross-sectional study.
There may have been recall bias, underestimation, and overestimation of some experiences reported by the respondents but this was minimized by employing them to provide truthful responses and the fact that the information would be kept confidential and used for the purpose of the study alone.
In conclusion, findings in this study showed that prevalence of antenatal depression in Abeokuta North LGA is high at 24.5%. It peaked in the first trimester and slightly decreased with increasing trimester.
Various risk factors and predictors of antenatal depression were determined, and these were attending antenatal care in public facilities, gender based abuse or violence, intake of alcohol in pregnancy, young age, premarital pregnancy, unplanned pregnancy, illiteracy, history of previous caesarian section, coexisting medical conditions, and large family size.
Finally, the health seeking behaviour for antenatal depression among depressed women was determined. It was identified that involvement of clerics, husbands, family members, and friends in the management of antenatal depression was necessary to curb the menace. Some recommendations were made on how to tackle antenatal depression.
The high prevalence of antenatal depression in this study is of public health concern; hence, health education and awareness campaigns should be embarked on to enlighten the populace about how to identify antenatal depression symptoms and the dangers of not getting it treated early. Edinburgh Postnatal Depression Scale (EPDS) screening should be introduced as part of antenatal care assessment in both private and public health facilities to help identify women with antenatal depression or at risk of developing it, and an invite should be sent to psychiatric team for comanagement. Measures such as education and awareness campaigns targeting reducing or prevention of risk factors should be embarked on. Successful reduction or elimination of risk factors will definitely reduce prevalence of antenatal depression.
Government and hospital management should introduce screening for depression as part of routine antenatal assessments in both public and private health facilities. Each pregnant woman should be screened at least thrice for depression before childbirth, with one screening in each trimester. Early registration for antenatal care especially in the first trimester should be encouraged since antenatal depression peaks in the first trimester. Community awareness campaigns should be embarked on by the state public health sector to educate the society on antenatal depression and its associated risk factors, dangers associated with untreated depression, and the need to get prompt help. Counseling on alcohol prevention should be initiated in all health facilities. Government should enact laws making gender based violence illegal and punishable as this would reduce prevalence of antenatal depression due to gender based violence.
Family planning should be encouraged by the doctors, especially after childbirth, to avoid unplanned and unwanted pregnancy and child spacing, limit family size, and prevent sexually transmitted diseases. Prompt treatment of coexisting medical conditions could help to reduce depressive symptoms and literacy education should be initiated by the state government as this has been found to reduce depressive symptoms. Social support network should be established which provides an avenue for all the at-risk and depressed women to come together and share their challenges and coping mechanisms. Further study is recommended, especially a community based one, to determine the gravity of antenatal depression in the community as this study might have underestimated the prevalence since it was hospital based.
The authors declare no competing interests.
The authors are grateful to Dr A. T. Salawu for the invaluable advice he offered to improve the conduct of this research. Their sincere appreciation goes to the staff of the health facilities for their assistance and to the pregnant women attending the health facilities for their cooperation.