Background

Maternal mental disorders are illnesses that occur during pregnancy or in the first year after childbirth; the most common mental illness during this period is maternal depression, also called perinatal depression (Gelaye et al. 2016; Sparling et al. 2017; Biratu and Haile 2015; World Health Organization (WHO) 2012). According to the World Health Organization, mental disorders worldwide have been documented as a top priority among the most dominant and neglected diseases (World Health Organization (WHO) 2012; Fisher et al. 2012; GBD 2017). It affects approximately 322 million people globally; out of those affected 29.19% comes from Africa (World Health Organization 2017) and its 50% higher in females than males (Saeed et al. 2016). Maternal depression is a major public health problem that affects mother’s wellbeing and an attitude about life (Sparling et al. 2017; Stein et al. 2014). In low- and middle-income countries (LMICs), most maternal depression remains unnoticed and untreated; this may be due to the reason that depressive symptoms often cannot be differentiate between normal physiological changes during pregnancy and other pathological changes, and that screening of maternal depression is not part of service delivery in antenatal clinics in LMICs. It is documented that about 12.5–42% of pregnant women and 12–50% of mothers of newborns in LMICs screen positive for symptoms of depression (Shidhaye and Giri 2014); and also documented that about 76% and 85% of individuals suffering from mental illnesses in low- and middle-income countries do not receive treatment for the disorder (World Health Organization 2019). In pregnancy and early years of an infant’s life, maternal depression and anxiety can cause substantial problems to the mother and her infant (Surkan et al. 2011). It can cause sadness and low energy, low motivation, and poor parenting (Guo et al. 2013). It can also lead to lack of hope, self-blame and doubt, confusion, and guilt of not being a good parent (Stein et al. 2014; Shidhaye and Giri 2014). Suicide is an ever-present risk with depression, along with adverse effects on infant growth and birth weight (Surkan et al. 2011; Qiao et al. 2012).

The social determinants of health explain the risk factors of depression which include social, psychological, and biological factors (World Health Organization (WHO) and Calouste Gulbenkian Foundation 2014). Nutrition and lifestyle measures are the biological bases of mental illness, and nutritional deficiency is a factor that has been given consideration, among other theories about the causes of depression; research-based evidence reveals that patients with depression have altered levels of monoamine neurotransmitters (Jacka et al. 2017; Leung and Kaplan 2009). According to Rechenberg and Humphries, the three mechanisms that bring about depression include (a) low dopamine, serotonin, and norepinephrine levels in the brain; (b) neuro-membranes that have been altered and the polyunsaturated fatty acids impact on the membranes; and (c) hormones, specifically hormonal changes which occur during and after pregnancy; all of these pathways are affected by particular nutrients and could be corrected by nutritional interventions (Rechenberg and Humphries 2013).

Nutritional Science, Brain, and Mental Health

Nutrition is a science of food and its relationship to health (Liu et al. 2015; Kaur et al. 2014). It is already known that nutrition is fundamental to brain health in regulating neurotransmitters to function well, and that the neurotransmitters failure has been identified as a key element that brings connection between nutrition and depression (Rechenberg and Humphries 2013). It is also true that perinatal mood disorders (depression), leads to unhealthy behavioral changes which have serious and lasting consequences to both mother and child, that is why there is no health without perinatal mental health (Stein et al. 2014). The relationship between nutrition and brain functions has been found to be intricately intertwined for long period of time in history almost 100 years back; strong connection between nutrition and mood has been identified for B-complex vitamins, including vitamin B6, and, vitamin B-12, folate, magnesium, calcium, iron, zinc, and omega-3 types (Kennedy 2016; Gómez-pinilla 2010; Bodnar and Wisner 2015). Other nutrients commonly associated with mental health include antioxidant vitamins, such as C and E22, and bioactive substances found in foods (Rechenberg and Humphries 2013; Larson and Yousafzai 2017; Opie 2017). These nutrients are mostly available in healthy diets, such as those that include dark green leafy and orange or red-colored vegetables and whole-grains and protein sources (Davison et al. 2012).

The properties and functions of these nutrients have been investigated with respect to their role in a number of ways in which they can affect neural and endocrine pathways, and understanding how their deficiencies may contribute to the pathophysiology of depression. For example, Leung and Kaplan review (Leung and Kaplan 2009) report folate as a vitamin that is required for the biosynthesis of the three monoamine neurotransmitters: the serotonin, dopamine, and norepinephrine; the deficiency of this vitamin may affect the production of the neurotransmitters leading to depression. A study by Kennedy reported vitamin B6 in the involvement of neurotransmitter pathways; it is a cofactor in the production of serotonin from tryptophan, and that low plasma level of B6 has been associated with depression (Kennedy 2016). Vitamin B-12 has neurological function, and it is also a cofactor in the production of neurotransmitters (Rechenberg and Humphries 2013; Ford et al. 2018; Meihua et al. 2017). Other functions of B12 include forming red blood cells and maintaining nervous system. Zinc, is an essential nutritional element which plays many key roles including enzyme catalysis, cell signaling, DNA replication, and transcription and therefore is essential for neural development in learning and memory function as well as mood stability (Meihua et al. 2017). Zinc has also been used as an anti-depressant (Ranjbar et al. 2013). Another important nutritional element is polyunsaturated fatty acids (PUFAs), particularly n-3 PUFAs, which are the building blocks for health brain function and development. Epidemiological evidence has established that low consumption of n-3 PUFA is associated with mood disorders (Reimers and Ljung 2019). This is due to the fact that brain has the highest concentration of lipids after the adipose tissue; the brain contains 50–60% lipids concentration which forms the dry weight of the brain, and the brain requires particularly PUFAs from the 6 and 3 PUFAs families; therefore, the decrease in their concentration leads to imbalances of neurotransmitters resulting to mood disorders (Larrieu and Layé 2018).

Nutritional Needs During Pregnancy

Evidence from research shows that women of childbearing age are vulnerable hence suffer from nutritional deficiencies, becoming at high risk of developing depressive disorders among other complications (Bodnar and Wisner 2015). Pregnancy is a period in particular, that has attracted special attention with respect to the occurrence of depression (Gernand et al. 2016). This may be due to the reasons that during pregnancy, nutritional needs are upraised to meet the increased demands for fetus development and other metabolites during pregnancy; this may result in depletion of maternal nutrient stores, poor nutrients concentration in the blood and brain subsequently neurotransmitter imbalances and mood disorder (Sparling et al. 2017; Rechenberg and Humphries 2013). To mention few example, folate (folic acids) is important in the production of blood and protein; it reduces the risk of neural tube defects (which is the birth defect of the brain and spinal cord); it plays a crucial role in many metabolic reactions such as the biosynthesis of DNA and RNA, methylation of homocysteine to methionine, and amino acid metabolism (Mousa et al. 2019). The recommended intake of folate increases during pregnancy from 200 to 400 mcg per day (Lowensohn et al. 2016). When pregnant women do not meet their daily recommended allowance for this nutrient, they become deficient. A serious decrease in nutrient stores throughout pregnancy and a lack of immediate recovery after childbirth increase a woman’s risk of developing depression (Bodnar and Wisner 2015). Thus, pregnancy represents a unique opportunity in life with considerable possibility to influence maternal health and the health of the next generation (O'Neil et al. 2014). Thus, to say optimal nutrition is necessary and the diets should be balanced, not only in terms of macronutrients proteins, carbohydrates, and fats, but also in terms of micronutrients vitamins and minerals, to reduce nutritional deficiencies and inadequacies (Rechenberg and Humphries 2013).

In LMICs, pregnant women are even at higher risk of poor nutritional deficiencies as a result of poverty, food insecurity, lack of adequate financial or family support, gender-based violence, frequent infections, and frequent pregnancies (Chaparro et al. 2014; Salam et al. 2015; Lindsay et al. 2012). Maternal malnutrition is evident and accounted for by the facts that between 5 and 20% of African women have a low body mass index (BMI), an outcome of long-lasting problems of lack of enough food, and across the continent, the prevalence of anemia ranges from 21 to 80%; similarly, high deficiencies in both vitamin A and Zn deficiency levels have been experienced (Lartey 2008). WHO estimates that globally, over two billion people are at risk of vitamin A, iodine, and iron deficiency; other micronutrients deficiencies of public health concern are zinc, folate, and B vitamins (Bailey et al. 2015). Studies from Kenya and Nigeria, for example, have revealed a high prevalence of both under- and over-nutrition, as well as nutrient deficiencies, including iron, folate, vitamin D, and vitamin A, that result in obstetric complications, hypertension, anemia, neural tube defects, night-blindness, low birth weight, and maternal and perinatal mortality (Lindsay et al. 2012; Obwocha et al. 2016). The micronutrients discussed above are very crucial to brain health, and their deficiencies increases the risks of mental disorders and other non-communicable diseases among women in the reproductive years. The double burden of malnutrition also co-exists in developing countries due to poverty poor eating behavior and eating habits, that lead to increased undernutrition and over nutrition (Kimani-Murage et al. 2015). Women are as twice vulnerable and susceptible to the double burden of malnutrition because of their high nutritional needs during pregnancy and lactation especially in the context of gender inequalities (Nguyen 2019). In LMICS where people lack enough food, there is a tendency of consuming high quantities of energy giving food due to the fact that they are cheap and easier to obtain as well as their capacity to satisfy hunger. These scenarios result in over consumptions of mostly carbohydrates, fats, and sweet drinks leading to growing rates of obesity among perinatal women that can be transferred to their off springs.

Objectives

Nutrition deficiencies are common among pregnant and lactating women in LMICs; at the same time, levels of maternal depression are extremely high among members of this group suggesting some connection between the two. The objective of this review is to determine the associations between nutritional deficiencies and maternal depression and identify the role of diet in depression to facilitate further research.

Methods

Search Strategy

A literature search included PubMed databases and Google Scholar search engine published from June 2008 to June 2019 and published in English. Medical subject heading terms were used to identify all relevant studies. The first search combined nutritional deficiency terms with maternal depression terms, while the second combined diet quality terms with depression terms and maternity terms separately. All titles and abstracts identified by the search were screened, then reviewed the full text, which were potentially eligible articles for inclusion.

Study Criteria

Studies considered for inclusion in this review were full-text articles and abstracts which consisted of cross-sectional study designs, cohort, studies, randomized control trials, and longitudinal studies that examined the association between nutrition and maternal depression, dietary practice, role of diet in preventing depression; and if they presented measures of association between nutritional biomarkers during or after pregnancy, and depression during pregnancy or up to 1-year postpartum. We excluded studies that examined nutrient deficiencies in animals, examined the effects of additives on mental health, examined emotional or binge eating, studies that were published in a language other than English, and studies that assessed hormones or other compounds synthesized by the body but not directly affected by dietary intake. There were no limitations placed on age due to known high rates of adolescent pregnancies across developing countries or the timing of pregnancy.

The Search Details

(“malnutrition”[MeSH Terms] OR “malnutrition”[All Fields] OR (“nutritional”[All Fields] AND “deficiencies”[All Fields]) OR “nutritional deficiencies”[All Fields]) AND (“mothers”[MeSH Terms] OR “mothers”[All Fields] OR “maternal”[All Fields]) AND (“depressive disorder”[MeSH Terms] OR (“depressive”[All Fields] AND “disorder”[All Fields]) OR “depressive disorder”[All Fields] OR “depression”[All Fields] OR “depression”[MeSH Terms]) AND middle [All Fields] AND (“poverty”[MeSH Terms] OR “poverty”[All Fields] OR (“low”[All Fields] AND “income”[All Fields]) OR “low income”[All Fields]) AND countries [All Fields] AND Mesh Terms: Role; diet; mothers; depression; depressive disorders (“2009/06/28”[PDat]: “2019/06/25”[PDat]).

Data Extraction

The data extraction was conducted by two reviewers (a data collector and the first author (BM)), who independently extracted the data addressing the criteria of the study. We extracted the following key information from those articles that were eligible for inclusion: the author, sample size, screening instruments (dietary measure, and mental health measure), key findings, and the limitations of the study. All the information of the eligible articles was put into a spreadsheet as indicated in Table 1 Additional file 1

Table 1 Studies included in the review on the role of diet in the prevention of maternal depression
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Quality Assessment

Quality assessments of all of the eligible studies were evaluated for methodological quality and appropriateness for inclusion, based on a set of pre-determined criteria derived from the National Institutes of Health (NIH) Quality Assessment Tool of Systematic Reviews and Meta-Analyses in PRISMA guidelines.

Search Outcomes

The initial search strategy identified 1250 citations; out of these, 42 were excluded because of duplication, leaving 1,208 relevant studies. Out of those studies, 1,132 were excluded based on information available in the abstract and title that did not fit the objective of this review; the remaining 76 articles were assessed for eligibility. On examination of the full-text articles, 51 studies did not fulfill inclusion criteria and were afterward excluded; only 25 studies were eligible for final analysis, as indicated in Fig. 1.

Fig. 1
figure 1

Flow chart of study selection. Flow diagram: study selection process on the role of diet in prevention of maternal depression

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Data Analysis

Studies that were included for analysis were separated by study design, sample size, objectives, screening instruments, outcomes, and limitations of the study. Using these stratifications, we calculated proportions of studies that demonstrated positive and negative associations between diet and maternal depression.

Results

Overview of Studies

A total of twenty-five studies were eligible for final analysis. Of the twenty-five studies that were reviewed, thirteen studies were cross sectional, eight were prospective cohort studies, and four studies were intervention studies. About 95% of these studies reported positive associations between nutrition deficiencies, poor diet, and maternal depression; only 5% reported that there were no associations between nutrition and depression. Much of these associations were cross-sectional which represented 52%; prospective cohort studies were 32%, and intervention studies were 16%.

Screening Instruments: Depression Measures

Previous researches have used different tools to measure maternal mental disorders. Out of all the tools used, Edinburgh Postnatal Depression Scale (EPDS) was the most commonly used tool for screening of maternal depression, where eight studies out of the reviewed twenty-five, used it. Other assessment tools that were used included the Perceived Stress Scale and the Prenatal Distress Questionnaire (Singh et al. 2017); The Expanded Mini-International Neuropsychiatric Interview (Abrahams et al. 2018); General Health Questionnaire (GHQ-12) (Jacka et al. 2010); Clinical interview (SCID-I/NP), psychiatric history (Khalid et al. 2016); The Kessler Psychological Distress Scale (K-10) (Lukose et al. 2014); Depression (CES-D) Scale (Akbaraly et al. 2009); Clinical interview (Structured Clinical Interview for DSM-IV-TR (Jacka et al. 2012); Montgomery–Åsberg Depression Rating Scale (MADRS) (Jacka et al. 2017) and Xhosa version of the 10-item Edinburgh Postnatal Depression Scale (Tsai et al. 2016); and lastly Depression Anxiety and Stress Scale 21 depression subscale; DASS-21-D (Francis et al. 2018).

Screening Instruments: Dietary Measures

The tool that was mostly used for dietary intake measure was Dietary 24-h recalls method and Food Frequency Questionnaire (FFQ); other tools included Automated Self-Administered 24-hour dietary recall (ASA24) (Singh et al. 2017); dietary knowledge and practices questionnaire (Nana and Zema 2018); dietary patterns questionnaires (Akbaraly et al. 2009); 7-day food diary; and Dietary Quality Index–Pregnancy (DQI-P) (Fowles et al. 2012); Nutrition clinical and biochemical (Lukose et al. 2014); dietary intakes 3-day food diaries and dietary patterns (Teo et al. 2018); single-item food insufficiency measure (Tsai et al. 2016); and the CM-700D Konica-Minolta Spectrophotometer, which measures the light in the participant’s skin reflected and skin yellowness and the quantity of flavonoids (chemicals from fruit and vegetables) in their diet to predict plasma carotenoid levels following diet intervention (Francis et al. 2018).

Discussion

Association Between Nutrition and Maternal Depression

Most studies in this review consistently associated poor quality prenatal diet with poor maternal mental health. A study by Paskulin and colleagues in Brazil found a high prevalence of major depressive disorder among women with low fruit intake (43%, PR 1.43, 95% CI 1.04–1.95) and high sweets and sugars intake (91%, PR 1.91, 95% CI 1.19–3.07) (Paskulin et al. 2017). A study by Singh and colleagues, in Latina, evaluated the prevalence of nutritional deficits in pregnant teenagers and assessed the associations among micronutrient dietary intake and depression; results show that more than 50% of pregnant teenagers had an inadequate intake of folate, vitamin A, vitamin E, iron, zinc, calcium, magnesium, and phosphorous; these are micronutrients that are very crucial to brain health (Singh et al. 2017). In Ethiopia, Nana and Zema (Nana and Zema 2018) reported that more than half of the pregnant women (60.7%) in the study had poor dietary practices which they attributed to maternal poor health. In a study by Jacka and colleagues, in Australian, the relationship between high-prevalence mental disorders and habitual diet was studied; the results demonstrated an association between habitual diet quality and high-prevalence mental disorders (Jacka et al. 2010). Again, Williams and colleagues in Australian reported that low socioeconomic status group had a 2.0-fold increased odds of a current mood disorder compared to the secure food group (Khalid et al. 2016). Baskin and colleagues (Baskin et al. 2017) in New Zealand found that unhealthy diet was associated with increased rates of depressive symptoms. Fowles and colleague (Fowles et al. 2012) in Austin, Texas examined the relationships among distress social support and eating habits with dietary quality in low-income pregnant women and found that poor eating habits had a direct effect on psychosocial distress, and poor eating habits contributed to inadequate dietary quality. A study by Dad and Desyibelew (Dadi and Desyibelew 2019) determined the extent of undernutrition among pregnant mothers in Gondar town, Northwest Ethiopia; Results indicate 14.4% (95% CI: 12.3–16.7) of pregnant mothers were undernourished.

Role of Diet in Understanding Maternal Depression

A well-balanced diet contains thousands of nutrients that are helpful to our bodies and all nutrients are normally consumed from various sources of food in meals (Cetin and Laoreti 2015). Diets with abundance of vegetables, alongside with animal protein, legumes, fruits, nuts, and whole grains, have been evaluated in research and were found to contain nutrients that improve mental health (Jacka et al. 2017). A cohort study of pregnant women by Chatz and colleagues in Greece (Chatzi et al. 2015) investigated dietary patterns and depression during pregnancy and found that high adherence to a health-conscious diet, which is high in vegetables, fruit, pulses, nuts, dairy products, fish, and olive oil, was associated with lower EPDS scores β-coefficient = − 1.75, p = 0·02). Prospective cohort study by Akbaraly and colleague (Akbaraly et al. 2009) examined the association between dietary patterns and depression using an overall diet approach, and found an association between an unhealthy diet and mental health problems; unhealthy diet score, were two times likely to be more symptomatic (OR 2.10, 95% CI: 1.38–3.20).

A randomized controlled trial named “The SMILES trial” tested the efficacy of a 12-week dietary intervention in the treatment of major depressive disorders, and results demonstrated that dietary improvement was a viable treatment strategy for treating major depression (Jacka et al. 2017). Francis and colleagues (Francis et al. 2018) conducted a RCT to examine whether young adults with elevated depression symptoms would comply with a brief, 3-week diet intervention and whether this can improve symptoms of depression; results indicated that Diet Change (DC) group improved from the elevated range (i.e., > 16) to the no clinical significance range, in the Centre for Epidemiological Studies Depression scale-Revised (CESD-R) score, but remained elevated in the habitual diet (HD) group across baseline and day 21. This difference was significant, with the DC group having significantly lower CESD-R scores on day 21 compared to the HD group, controlling for baseline CESD-R scores (F[1,75] = 7.792, p = 0.007, Cohen’s d = 0.65. Additionally, when the ANCOVA was rerun, controlling for age, gender, physical activity, and baseline BMI, the significant group difference at day 21 remained (F[1,71] = 7.091, p = 0.010. A study by Jacka and colleague (Jacka et al. 2012) examined the relationship between the dietary intakes of three elements (magnesium, folate, and zinc) and found that increase in the intake of these three was associated with reduced odds for major depression (zinc: OR = 0.52, 95% CI: 0.31 to 0.88; magnesium: OR = 0.60, 95% CI 0.37–0.96; folate: OR = 0.66, 95% CI 0.45–0.97). A study by Saeed and colleague (Saeed et al. 2016) found that antenatal depression increases the risk of poor Healthy Eating Index rates on the mothers and neonatal outcomes consisted of fetal growth retardation, preterm birth, and low Apgar score. Another study by Pina (Pina-Camacho et al. 2015) found prospective association between higher prenatal maternal depression symptoms to be with higher unhealthy diet, both during pregnancy and the postnatal period, which was also associated with higher child dysregulation up to the age of 7 years. A study by Poorrezaeian and colleague (Poorrezaeian et al. 2017) determined the relationship between the dietary diversity score (DDS) and stress and depression in women. Results indicate that a total of 31.4 and 25.8% of the subjects suffered from depression and stress, respectively, and a one-unity dietary diversity score increase was associated with a 39% reduction in the risk of severe depression.

However, not all studies have shown an association between nutrition and maternal depression clearly. A prospective study by Teo and colleagues (Teo et al. 2018) examined the associations of dietary patterns during the confinement period in a multi-ethnic Asian cohort with postpartum depression) and anxiety. The study identified four dietary patterns: traditional-Indian-confinement diet; soup-vegetables-fruits diet; traditional-Chinese-confinement diet; and eat-out diet with maternal mental health. The results did not show an association between traditional-Chinese-confinement diet and eat-out diet with maternal mental health, but the association was detected between traditional-Indian-confinement diet and soup-vegetables-fruits diet, with reduced depression symptoms. This may be due to the reason that the traditional-Indian-confinement diet comprises legumes and pulses; these foods are rich in B-group vitamins that are crucial for the synthesis of monoamine neurotransmitters and may have helped to establish protection against depression symptoms. A prospective cohort study by Lukose and colleagues (Lukose et al. 2014) examined the associations between maternal depression and nutrients intake using biochemical measurements and food frequency questionnaire; the results showed that nutrient intakes, serum vitamin B12, methyl malonic acid, homocysteine, and red cell folate levels were not associated with measures of depression.

Methodological Strengths and Limitations

Study Design

Most of the studies in this review were cross sectional; the strength of these cross-sectional studies is that they established relationship between maternal mental disorders and the role of diet intervention in preventing the disorders. However, as a limitation, cross-sectional study design does not facilitate the establishment causal relationship between dietary factor and mood. On the other hand, interventional and prospective longitudinal studies are recommended as they have the capacity to establish causal relationship between the dietary factor and mood disorders (Singh et al. 2017; Paskulin et al. 2017). The strengths of these designs are that they give an opportunity to account for the effect of exposures during pregnancy and early life measures prospectively within the cohort that enables establishment of the relationship between exposures and outcomes. Bias issues were also observed in some cohort studies in this review, where there was failure to blind the participant in the intervention group and comparison group, which may affect on the results of the interventions (Jacka et al. 2017).

Sample Size Limitations

Sample size and short duration of the study were among the limitations found among the study reviewed in this review. For example, the study by Jack FN and Null et al. (Jacka et al. 2017; Null et al. 2017) had small sample size which reduces the ability of the sample to be representative and cannot be generalized to the general population. Low participation rate was another limitation observed in a cohort study by Chatzi and colleague (Chatzi et al. 2015) in which a big number of participants did not participate in the follow-up. This resulted in a final sample that could not meet the representative threshold.

Screening Instrument Limitations

Although EPDS is an established and widely used screening tool for maternal depression with high specificity and sensitivity, it is not a definitive diagnosis, hence, the inherent limitation of using this tool. Assessments of depression symptoms with self-administered EPDS, rather than definite case based on clinician-administered structured diagnostic interview, have its limitations, that cause unreliability in results. (Chatzi et al. 2015). Another limitation found was using tools that are not validated in a given population; this may lead to unreliable results, and an example is the study by Singh and colleague (Singh et al. 2017) who used Reynolds Adolescent Depression Scale, Second Edition (RADS-2), the psychosocial measures tool which was not validated in a Latina population.

Dietary Measures Strength and Their Limitations

The 24-h recall method is considered to be cheaper and easier than other techniques and has been found to yield reliable information if carefully planned and implemented (Gibson et al. 2017). This review supports such observations albeit limitations to be considered when using this tool. According to Naem and colleague (Naem et al. 2014), a 24-h dietary recalls resulted in under- or over-reporting of food intake and possibilities of participants to provide their desire responses. A study by Singh (Singh et al. 2017) indicated that conducting only one 24-h dietary recall in a study can reduce the internal validity of the findings; however, it has been noted that a one-time 24-h recall reduces errors compared to the longer interval of recollection. On the other hand Automated Self-Administered 24-h dietary recall (ASA24) method is more accurate than administered 24-h recall. On the other hand, most of the information obtained through 24-h recall may be a source of both recall and social desirability bias when self-reported because the data does not take into account issues concerning accuracy of responses (Obwocha et al. 2016). The Food frequency questionnaire (FFQ) was used often among the studies reviewed; this tool is designed to assess habitual diet by asking about the frequency with which food items or specific food groups are consumed over a reference period; however, FFQ has poor capability to estimate the actual ingestion which is one of the limitations of the instrument. Chatzi et al (Chatzi et al. 2015) observed that the assessment of dietary intake in pregnant women is complicated because of various factors depending on the period of pregnancy. According to Desta and colleagues (Desta et al. 2019), FFQ may not give the exact figure of the dietary diversity due to a recall bias and being self-reported. According to Nana and Zema (Nana and Zema 2018), lack of standardized FFQ questionnaires at national level, where the study is conducted, is a limitation that can lead to failure in assessing food intake in terms of specific nutrients consumed hence results may be unreliable.

The limitation of this review includes shortage of available literature and indexed articles on the association between nutritional deficiencies and maternal depression, the role of dietary protective power to prevent depressive disorders in lower income countries; due to this reason, this Systematic review was conducted on only the current available limited literature that associated nutrition and perinatal depression. Also in this review, the study population of the articles reviewed comprised mostly the women from low- and middle-income contexts; now, the focus on low-income women and middle class limits the application of the findings to women living in high socioeconomic contexts. However, focusing on low-resource contexts is important as these women are most likely to suffer most from nutritional deficiencies and experiences of adverse pregnancy outcomes.

Conclusion

Results demonstrate an association between diet quality and maternal mental outcomes. Research has provided evidence that food and nutrition interventions are some of the most promising intercessions for mental health illnesses. The findings derived from this review suggest that nutritional interventions should be tested to determine their efficacy in prevention and treatment of maternal mental health conditions as it is a major public health issue today. This can offer a window of opportunity to reduce the risk of maternal mental disorders in mothers and offspring alike. Therefore, as a recommendation to substantiate these associations between diet quality and mental health, longitudinal studies need to be conducted to confirm the preventive nature of nutrition to prevent mental disorders and other chronic diseases.