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 Table of Contents  
ORIGINAL ARTICLE
Year : 2022  |  Volume : 43  |  Issue : 2  |  Page : 108-115

Impact of maternal depression and social factors on child’s nutritional status: a case–control study in Egypt


1 Department of Neurology and Psychiatry, Faculty of Medicine, Minia University, Minia, Egypt
2 Department of Pediatrics, Faculty of Medicine, Minia University, Minia, Egypt

Date of Submission28-Nov-2021
Date of Decision07-Dec-2021
Date of Acceptance13-Dec-2021
Date of Web Publication24-Jun-2022

Correspondence Address:
Maha A Hassan
Department of Psychiatry, Neurology and Psychiatry, Faculty of Medicine, Minia University, Minia 61111
Egypt
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Source of Support: None, Conflict of Interest: None


DOI: 10.4103/ejpsy.ejpsy_35_21

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  Abstract 


Background Malnutrition is a primary cause of child morbidity. Maternal depression affects children’s health, especially nutrition.
Aim This study aimed to explore the effects of maternal depression and social factors on children’s nutrition.
Patients and methods A case–control study was carried out on 100 children and their mothers: 50 malnourished children and 50 age-matched and sex-matched healthy-control children. Anthropometric measurements of children were done and transformed into weight-for-age and weight-for-height Z-scores. Screening of depression in mothers was done using Symptom’s Checklist 90-Revised (SCL90-R) Depression dimension. Mini-Mental State Examination (MMSE) was used to assess maternal cognitive functions.
Results Thirty-eight percent mothers of malnourished children were depressed compared with 12% mothers of healthy children. The difference was statistically significant (P<0.05). Statistically significant differences were found regarding maternal age at marriage, education, working status, crowding index, and family income between groups (P<0.01). Mothers of malnourished children had cognitive impairment than controls (P<0.001). The Z-score of malnourished children was positively correlated with breastfeeding duration, maternal age at marriage, education, working status, family income, and other social parameters; and negatively correlated with crowding index and gastrointestinal tract (GIT) morbidity, indicating that malnutrition increases with short duration of breastfeeding, younger maternal age at marriage, low education, bad working status, low income, and high crowding index.
Conclusions Mothers of malnourished children have more depressive symptoms and impaired cognitive functions than the controls. Maternal age at marriage, education, family income, and crowding index are predictive variables affecting children nutrition.

Keywords: depression, malnutrition, SCL-90 R


How to cite this article:
Hassan MA, Bebars GM, Taha SM. Impact of maternal depression and social factors on child’s nutritional status: a case–control study in Egypt. Egypt J Psychiatr 2022;43:108-15

How to cite this URL:
Hassan MA, Bebars GM, Taha SM. Impact of maternal depression and social factors on child’s nutritional status: a case–control study in Egypt. Egypt J Psychiatr [serial online] 2022 [cited 2022 Aug 18];43:108-15. Available from: http://new.ejpsy.eg.net/text.asp?2022/43/2/108/348148




  Introduction Top


The health and well-being of children is inevitably related to their early social and emotional experiences. Feeding and caring for the young is primarily the mother’s responsibility, therefore, poor maternal physical or mental health can negatively affect nutrition, physical, and psychological health of children (Cummings and Kouros, 2007).

Previous reports have demonstrated that the absence of natural motivation, enthusiastic, and emotional support has a similar significance like supplements’ inadequacy on the developing cerebrum. When both the unfriendly elements are consolidated, the effect on youngsters is serious (Musaiger et al., 2011).

The role of maternal depression in the development of the child has been questioned in research (Surkan et al., 2014).

Maternal mental health has been disregarded in both youngster nourishment and advancement projects and it might be the missing connection in maternal and child-health programs.

We aimed to study the relationship between psychological and social aspects of mothers and their children nutritional status.


  Patients and methods Top


This study is a case–control study, carried out from March 2018 to March 2019 at Children & Maternity University Hospital after study approval from the ethical committee of the Minia Faculty of Medicine. The sample was designed to include two groups of children and their mothers that enrolled from nutrition-rehabilitation unit and from the general clinic of the same hospital after informed oral consents from their caregivers.

The first group included 50 children diagnosed as PEM (protein energy malnutrition) with Z-score weight for height less than−2 SD (as moderate PEM) and less than −3 SD (severe PEM). They were recruited from nutrition-rehabilitation unit of the hospital during admission with their mothers. The second group included children who were in a good nutritional state, and were recruited from the general clinic during medical consultation about acute illness (e.g. otitis media, common cold, etc.) in the same hospital. Children who were deaf, mute, or blind, also children suffering from chronic illness, motor, or mental disability were excluded from the study. Mothers who were deaf, mute, blind, or having chronic medical illness, physical, or intellectual disability were also excluded.

The children and their mothers were subjected to detailed nutritional, developmental, and family history followed by physical examination of children. Mothers of both groups were screened using.

A − Symptom Checklist 90–Revised (SCL-90 R) is a rapid self-report questionnaire that consists of 90 items, and requires 10–15 min to be completed. It is used to assess the psychopathological burden as well as monitor the treatment efficacy. It covers nine symptomatic dimensions. Each item of the questionnaire is rated by the patient on a five-point scale of distress from 0 (none) to 4 (extreme) (Derogatis and Savitz, 2000). Depression dimension of the SCL-90 R that included 13 items, was applied to screen mothers for depressive symptoms. Most of the typical symptoms of depressive syndromes according to current diagnostic criteria are included. Symptoms of dysphoric mood and affect, as well as signs of withdrawal of life interest, lack of motivation, and loss of vital energy are represented. Feelings of hopelessness, thoughts of suicide, and cognitive and somatic correlates of depression are included. The current study utilized the Arabic version, which was translated by Dr. Abd El Rakib Ahmed El Behery (El Behery, 1984).

B − Mini Mental State Examination (MMSE) is a nontimed, 11-question measure that tests five areas of cognitive functioning: orientation, memory, attention, calculation, recall, and language. It takes only 5–10 min to administer (this makes it practical to use repeatedly and routinely). MMSE is divided into two parts. The first part requires vocal responses only and covers orientation, memory, and attention. The second part tests the ability to name, follow verbal and written commands, write a sentence spontaneously, and copy a complex polygon. The maximum score is 30. The total score of 23 or lower indicates cognitive impairment, and if the patient is physically unable to complete a task (e.g. draw a shape), that task is skipped and the total score is reduced by that. MMSE is effective as a screening tool for patients with cognitive impairment. When used repeatedly, it can measure changes in cognitive status (Folstein et al., 1975). It was translated from English to Arabic language (Rajeh et al., 1999). An oral and written consent was approved from all participants in this research.

Study approval was obtained from the ethical committee of the Faculty of Medicine, Minia University.

Statistical analysis

Data were entered and analyzed by SPSS version 19 (Statistical Package for the Social Sciences, IBM Inc., Chicago, Illinois, USA). Quantitative data were presented as mean and standard deviation, while qualitative data presented as frequency distribution. Comparison between groups was done by Mann–Whitney test and χ2 test. Spearman correlation was used. Probability of less than 0.05 was used as the cutoff for significance.


  Results Top


The age of studied malnourished children ranged from 2 to 36 months, mean±SD was 15.26±4.15, 48% were males, and 52% were females. The healthy-children group had ages that ranged from 6 to 48 months, mean±SD was 16.02±3.85, 60% (30) were males, and 40% (20) were females. No significant difference was found in birth order between both groups.

The well-nourished studied children (100%) were breastfed, but only 26 (52%) of malnourished children received breastfeeding (BF). Also, they have a shorter duration of BF than the controls (P<0.001). Malnourished children had significant recurrent attacks of gastroenteritis (P<0.004) and −72 (72%) have a significantly delayed motor development than well-nourished studied children (P<0.004) ([Table 1]). Forty four of the malnourished children were categorized as severe form according to WHO criteria, and 16 of them have edema in the dorsum of their feet.
Table 1 Criteria of studied children (malnourished children and normal-control children)

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Mothers of malnourished-children ages ranged from 14 to 28 years, while mothers of the control ages ranged from 20 to 34 years old. The mothers of malnourished children were significantly of younger age (P<0.00). Eighty-four percent of mothers of malnourished children were illiterate and the rest can only read and write. On the other hand, 4% of mothers of the control group of children were illiterate (P<0.001) and the majority (40%) attained secondary-school education. Seventy-six percent of mothers of malnourished children were not working, even those who work (24%) were manual workers, while 32% of the controls were not working at all and 20% have professional work (P<0.001). Fathers of malnourished children also were illiterate (44%) and 96% had manual work (P<0.001) in comparison with the well-nourished group where 40% graduated from universities and have professional work. The family income did not meet the expenses in 40% of families of malnourished in comparison with 4% only of healthy-children families. The social parameters, including sewage disposal, refuse disposal, crowding index, and source of water, were significantly poor in the malnourished group (P<0.001) ([Table 2]).
Table 2 Description of socioeconomic and demographic characteristics of the studied mothers

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Thirty-eight percent (N=19) of the mothers of malnourished children were depressed compared with 12% (N=6) of mothers of the controls screened by Depression Dimension of SCL-90 R and the difference was statistically significant (P<0.05). Moreover, Depression Dimension of SCL-90 R showed significant affection in mothers of malnourished children (P<0.002). The Mini Mental state testing the cognition in mothers showed 48% with mild and 44% with moderate cognitive impairment in mothers of malnourished. Only 8% in the other group have mild cognitive impairment and the rest of them (92%) have normal cognition. The difference was statistically significant (P<0.001) ([Table 3]).
Table 3 Comparison between mothers of malnourished and control children in depressive symptoms measured by SCL-90 R and cognitive functions measured by MMSE

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The nutritional status of studied children was positively correlated with breastfeeding duration, maternal age at marriage, maternal and paternal education, working status, family income, sewage disposal, refuse disposal, and source of water. This means that the severity of malnutrition increases with decrease of maternal age at marriage, low education, bad working status, low family income, other social parameters, and decrease in the duration of BF. Moreover, the nutritional status was negatively correlated with crowding index and GIT morbidity ([Table 4] and [Table 5]).
Table 4 Correlation between Z-score of studied malnourished children and socioeconomic status of their families

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Table 5 Correlation study between Z-score of the studied malnourished children and the depressive symptoms and cognitive functioning of their mothers

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  Discussion Top


Child-care practices are essential for appropriate development of youngsters. It has been proposed that poor maternal psychological well-being may unfavorably influence the child-care practice, debilitate development and advancement of the children (Faruque et al., 2008).

In the present study, children from both malnourished and the control groups are between 2 and 48 months of age, with slightly higher frequency of females among the malnourished group compared with that of the other group, but this difference did not reach any statistical significance. Some studies such as Santos et al. (2010) have demonstrated a higher occurrence of malnutrition in females and suggested social risk of gender bias in child care (Santos et al., 2010).

Our study revealed better practice and longer duration of BF among mothers of healthy children than malnourished children, with a significant positive correlation with good nutritional status. Our finding is similar to a study done in Bangladesh among malnourished children, 6–60 months old, 48.3% of infants got artificial feeding and just 7% were breastfed Iqbal Hossain and Kabir (1999). However, Martin (2001) in his commentary, showed inconsistent associations about longer duration of BF. Some ideas showed good benefits and few described drawbacks if BF was alone. He concluded that further studies are needed to clarify whether prolonged BF is a response to poor growth and ill health, or is a precursor of inadequate energy intake, malnutrition, and/or diarrheal diseases (Martin, 2001).

A significant motor delay in 28%, with 12% suffering delayed mental development, was encountered among studied malnourished children. This result is in line with (Grantham-McGregor, 1984) who demonstrated that longitudinal studies have additionally demonstrated that kids who had been stunted (height for age less than −2 SD below normal values) in the initial 2 years of life kept on indicating shortages in perception and school accomplishment from age 5 years to adolescence. In this manner, interminable undernutrition in early life appears to have durable results for mental health.

In the present study, there were significant differences between the two groups regarding maternal age at marriage, maternal education, and maternal working status, with no differences between the two groups regarding maternal age. Also, there were significant differences between the two groups regarding paternal education and working status, but there was no significant difference in paternal age at marriage or paternal age now, with significant positive correlations between these parameters and the better nutritional status in our studied children. These discoveries concur with the study done in Kampala, Uganda and the Moi Teaching and Referral Hospital in Eldoret, Kenya, looked at kids from zero to 60 months and three to 35 months separately and found a relationship among PEM and youthful (15–25 years), and single mothers (Ayaya et al., 2004). Likewise, Edward et al. (2013) reported that higher levels of unhealthy nutrition are related to a range of potential prenatal and postnatal confounds (i.e. poverty, teenage mother, low maternal education, parity, birth complications, substance use, criminal lifestyle, and partner cruelty toward mother) (Edward et al., 2013).

Maternal education is still an important issue to address. Illiterate mothers in our study were 84% among the malnourished group compared with 4% in the group of healthy children. Likewise, Christiaensen and Alderman (2001) found that female education had a positive and factually critical impact on nutritional status of their children (Christiaensen and Alderman, 2001). This can be explained by having better knowledge about better nutrition for their kids and nourishing practices (National Food Consumption Survey NFCS, 1999). However, Zottarelli et al. (2007) found that moms with high educational level had brought down danger of stunting than those with lower educational level (Zottarelli et al., 2007). It has been contended that education impacts the ability of mothers to decide concerning youngsters’ nutrition (Kandala et al., 2001). Then again, other studies did not discover a relationship among PEM and maternal level of education (Ayaya et al., 2004; Ashaba et al., 2015).

Social parameters such as family income, source of water, sewage disposal, and refuse disposal revealed significant differences between the two groups (P<0.001) with a significant positive correlation with the nutritional status. Our result is in line with a previous study that proved that some socioeconomic issues are linked to stunting such as the type of house (especially in urban areas): type of toilet in the home, fuel used in cooking, presence of refrigerator or stove, and television (Kleynhans et al., 2006). Also, Christiaensen and Alderman (2001) expressed that the ownership of a flush latrine in the house positively affects height (Christiaensen and Alderman, 2001).

Our study shows a significant difference and a negative correlation with the severity of malnutrition between the two groups and the crowding index that is matching with Kleynhans et al. (2006) and Mamabolo et al. (2005).

However, our study shows that 38% (N=19) of the mothers of the malnourished children were depressed as opposed to 12% (N=6) of mothers of the healthy children (P<0.05). Ashaba et al. (2015) reported results similar to our study, as 42% of mothers of malnourished children of their sample in southwest Uganda were depressed, compared with 12% of mothers of normal-weight children admitted to hospital for chronic illness (Ashaba et al., 2015). However, Haithar et al. (2018) reported higher prevalence of moderate-to-severe depression among mothers of malnourished children (64.1% compared with mothers of normal-weight children 5.1%) (Haithar et al., 2018).

The present study also shows significant affection in mothers of malnourished children in Depression Dimension measured by SCL-90-R compared with mothers of the healthy children (P=0.002). In spite of contrasts in the methodological approach, the present study confirms with past reports of a positive relationship between maternal psychological well-being and nutritional status of their children. Many studies revealed that children of depressed mothers are probably going to be underweight and stunted contrasted to offspring of moms without depression in both low- and high-income countries (Duarte et al., 2012; Husain et al., 2012; Edward et al., 2013; Surkan et al., 2014; Qamar et al., 2017; Haithar et al., 2018; Joshi and Raut, 2019). However, Lima et al. (2017) did not find associations between maternal depressive symptoms with child malnutrition or child excess weight. In their study, the prevalence of maternal depressive symptoms was 27.6% during gestation and 19.8% in the second or third year of the child’s life. The malnutrition rate was 6% and the excess-weight rate was 10.9% (Lima et al., 2017).

When studying the differences in cognitive function between mothers in the two groups, we found that 22 out of 50 (44%) mothers of malnourished children had moderate cognitive impairment in comparison with 46 out of 50 (92%) mothers of healthy children who had normal cognition (P<0.001), with no significant correlation with Z-score of studied malnourished children. Anoop et al. (2004), in agreement with our study, show that lower maternal intelligence can likewise influence the child’s nutrition (Lima et al., 2017). The explanations could be that lower ability to grasp the need to supplement nutritious food during the weaning period can result in malnutrition. Moreover, moms with lower intelligence will require basic guidelines and more prominent supervision (from relatives and group well-being specialists) to avoid malnutrition in their children. The study showed that the mental status of the studied mothers inversely affects child nutrition, as mothers whose mental health is poor are less able to care for themselves and their infants, whose survival, health, and development could be then compromised (Pangman et al., 2000). Few studies in the literature examined the relation between maternal cognitive functioning and children nutrition status.

Our study has some limitations. The sample size should be larger in order to generalize the results, especially the prevalence of maternal depression. Indeed, more extensive research to explore this issue is further needed.


  Conclusions Top


Several socioeconomic factors such as maternal age at marriage, maternal education, family income, and crowding index may attribute to malnutrition of children. Also, mothers of malnourished children were found to have more psychological (i.e. depression) and mental problems than those of the control group.

Management of maternal mental health may have a positive impact on children nutritional status. Maternal psychiatric health assessment by simple tools should be carried out at medical universities and local health facilities for early detection and treatment of disorders that negatively impact children’s health and well-being. Maternal education sessions focus on enhancing mother–child interaction and child-rearing practices should be applied at community clinics.

Acknowledgements

The authors would like to thank all mothers who agreed to participate in this study and gave us much of their precious time and patience.

All authors participated in a meaningful way in the preparation of the paper, M.A.H. had chosen the tools and planned the research, G.M.B. had filled the questionnaires and collected the data, and S.M.R.T. analyzed the data and participated in writing the paper after data analysis. All authors had participated in writing and revising the paper. All authors have meaningfully contributed to the work and approved the submitted paper. Each author believes that the paper represents honest work.

Financial support and sponsorship

Nil.

Conflicts of interest

There are no conflicts of interest.











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  [Table 1], [Table 2], [Table 3], [Table 4], [Table 5]



 

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