Skip to main content

Association between maternal decision-making and mental health and the nutritional status of children under 6 years of age in sub-urban Nigeria

Abstract

Background

We assessed the association between decision-making power and mental health status of mothers and the nutritional status of their children less than 6 years old in Ile-Ife, Nigeria.

Methods

This was a secondary data analysis of 1549 mother-child dyads collected through a household survey conducted between December 2019 and January 2020. The independent variables were maternal decision-making and mental health status (general anxiety, depressive symptoms, parental stress). The dependent variable was the child’s nutritional status (thinness, stunting, underweight and overweight). Confounders were maternal income, age, and education status, and the child’s age and sex. The associations between the dependent and independent variables were determined using multivariable binary logistic regression analysis after adjusting for confounders. The adjusted odds ratios (AORs) were determined.

Results

Children of mothers with mild general anxiety had lower odds of stunting than children of mothers with normal anxiety (AOR: 0.72; p = 0.034). Mothers who did not make decisions on children’s access to health care (AOR: 0.65; p < 0.001) had children with lower odds of being thin than those whose mothers made decisions on their access to health care. Children of mothers with clinically significant parenting stress levels (AOR: 0.75; p = 0.033), severe depressive symptoms (AOR: 0.70; p = 0.041) and who were not decision makers on the access of their children to health care (AOR: 0.79; p = 0.035) had lower odds of underweight.

Conclusions

Maternal decision-making status and mental health status were associated with the nutritional status of children less than 6 years in a sub-urban community in Nigeria. Further studies are needed to understand how maternal mental health is associated with the nutritional status of Nigerian preschool children.

Peer Review reports

Introduction

Mothers are the usually the primary caregivers for young children. The caregiving process can be complex and include many decisions and responsibilities around feeding a child, which is a key determinant of child malnutrition. Multiple maternal psychosocial stimuli may affect their ability to provide optimal nutritional care for their child [1,2,3]. One such psychosocial stimuli is depression, which is a mental health disorder.

Post-partum depression occurs in about 13% of women [4] and lead to poor parenting practices [2, 5]. It is associated with undernutrition in children because the depressed mother is unresponsive to the child, unable to form a secure attachment, and unable to provide a healthful diet for the child [6] often resulting in stunting [7]. Another psychosocial stimulus is general anxiety. Though a less consistent finding [8], chronic general anxiety may also present the same effect as depression [5, 9]. A third psychosocial stimulus is parental stress which promotes parent-centered that is counterproductive for the child’s optimal growth [10]. Though Harpham et al. [4] found no association between maternal mental health status and the child’s nutritional status in Ethiopia, an association was reported in Asia [1], suggesting possible regional variability in the impact of maternal mental health status on the child’s nutritional status.

In addition to maternal good mental health, higher levels of maternal economic status [11], more autonomous maternal decision-making ability [12] and higher maternal educational status [11, 13, 14] are factors positively associated with the nutritional status of children. Other factors associated with children’s nutritional status include the child’s sex - male children were more likely to be stunted [15]; and maternal age - children of mothers younger than 28-years had worse nutritional outcomes [16].

Although maternal psychosocial factors (general anxiety, parental stress, depressive symptoms, and empowerment status) affect children’s health behavior [17,18,19] and nutritional outcomes [20], there is no information on the associations between maternal related factors on the nutritional status of children in Nigeria [21, 22]. Yet, its plausible that there are associations between maternal mental health status and the nutritional status of children in Nigeria with the high prevalence of maternal mental health challenges, poor maternal decision-making power, and high prevalence of malnutrition in Nigeria. The prevalence of maternal perinatal depression ranges from 10 to 30% [23], and that of anxiety ranges from 16 to 39% [24]. In addition, 37% of children below the age of 5 years are stunted, 7% are wasted, 22% are underweight and 2% are overweight [25], with no significant changes in these figures since 2014 [26]. An estimated 2 million children under the age of five suffer from severe acute malnutrition, most of whom remain untreated [27].

Stunting, wasting and underweight are associated with increased risk for mortality in children while overweight is a risk factor for several debilitating diseases such as diabetes, heart disease, and some cancers [28, 29]. Yet, the risk of malnutrition may be lower for children whose mothers are empowered to make autonomous decisions about access to healthcare, household purchases and socialization [30,31,32]. This is because mothers with the ability to make independent decisions can direct household resources to the care of the children, enact their preferences in caring for and raising their children, and use their ability to socialize to increase awareness of, and access to health-promoting resources [33]. These ultimately lead to significant improvement in the health and nutritional well-being of the child [34] and reduces the odds of having children who are stunted, wasted or underweight [12, 35, 36].

There are several studies on the associations between poor maternal mental health and poor nutritional status of children [4, 37, 38]. There are, however, very few studies on the associations between maternal mental health and nutritional status of children in Nigeria [39] despite the high burden on children malnutrition in the country: Nigeria has the second highest burden of stunted children [27]. A study on the associations between maternal mental health and nutritional status of children acknowledges that there are geography and sociocultural contexts that affect the mental health [40] and the decision-making ability of mothers [41], as well as the nutritional status of children [42] and hence, the need for studies in Nigeria. Assessing the associations between maternal psychosocial status and children’s nutritional status will facilitate further studies on the pathways for these associations in the Nigeria context; and support the design of socio-cultural sensitive intervention programs to improve the psychosocial status of mothers and nutritional status of children.

In this study, we examined the associations between the decision-making and psychosocial status of mothers of children less than 6 years old in Ile-Ife Nigeria and the nutritional status of their children. We hypothesized that poor maternal autonomy (measured as lacking autonomous decision-making about health, household purchases and socialization), and poor maternal mental health status (general anxiety, parental stress, depressive symptoms) are associated with children’s poor nutritional status (thinness, stunting, underweight and overweight).

Methods

This was a secondary analysis of cross-sectional data collected from 1549 mother-child dyads to determine the association between maternal emotional health status and early childhood caries in children less than 6 years of age resident in Ile-Ife, Nigeria. Ile-Ife is a sub-urban agrarian community located in Southwestern Nigeria with an estimated population of 501,000 people.

Study participants, sample size and sampling procedure

Study participants for the primary study were mothers and their children aged 6 to 71 months old recruited between December 2018 and January 2019. Children present at the time of the survey, and for whom parental consent for study participation was obtained, were included in the study. The primary study excluded children with chronic medical conditions requiring prolonged use of free sugar containing medications, and those with medical conditions that increased their caries risk such as children with head and neck tumor that have undergone radiotherapy, children with Sjogren syndrome or children with HIV infection. The medical health status of the child was asked to determine their eligibility before enrolling them into the study.

The study participants were recruited using a three-level multi-stage sampling technique. The details of the sample size determination and sampling technique have been extensively described in a prior publication [43]. For this study, we computed a minimum sample size of 968 as adequate for determining the association between maternal psychosocial factors and children’s nutritional status using a malnutrition prevalence of 37% [25], error margin of 5%, and 95% confidence level. For regression, at least 300 participants were required to detect the smallest effect size based on Newsom’s method [44].

Data collection

The dependent variable for this study was the child’s malnutrition status (underweight and overweight, stunting and thinness) while the independent variables were the maternal psychosocial status (levels of general anxiety, parental stress and depressive symptoms) and decision-making status. The confounding variables were the child’s sociodemographic variables (children’s age and sex) and the maternal sociodemographic variables (maternal age, educational status and monthly income).

Nutritional status

Nutritional status was determined using the World Health Organization (WHO) AnthroPlus Software, which contains the WHO Reference 2007 for 5-19-year-olds and the WHO Child Growth Standard for 0-5-year-olds. This included height, age, and weight [45]. Data on height and weight was collected in line with the International Society for the Advancement of Kinanthropometry standard protocol [46]. Children removed shoes and any heavy clothes before having their height and weight measured. Height was measured once and to the nearest 0.1 centimeter with a portable stadiometer (Seca 217). The child stood barefoot, maintained the head in a neutral position, with the neck, spinal column and knees in physiological extension and the soles of both feet and buttocks touching the vertical backboard of the stadiometer. The horizontal bar of the stadiometer was lowered until it compressed the hair to the crown [47].

Weight was measured to the nearest 0.1 kg with a portable digital scale (Generic Electronic Digital Weighing Scale). The weighing scale was zero balanced before each child stepped onto it for each measurement. The weight was measured after the digital screen fluctuations stopped and while the child was standing erect and relaxed. The weight for infants was obtained by measuring the weight of the mother carrying the child, and then subtracting the weight of the mother [47].

Children whose height for age z-scores were below minus two standard deviations (SD) from the median of the WHO reference population were considered stunted, while those with z-scores of -2.00 to 2.00 were classified as normal. Likewise, children whose weight for age z scores were below minus two SD from the reference population median were considered underweight and those with z-scores > 2.00 were classified as overweight. Children whose Body Mass Index (BMI) for age z-scores were <-2.00 SD from the reference population median were classified as thin; those aged < 5 years with z-scores > 2.00 and > 3.00 were respectively classified as overweight/obese [48].

General anxiety

The 7-item Generalized Anxiety Disorder-7 scale was used to measure generalized anxiety disorder [49]. The instrument had a high sensitivity and specificity. It was used in Nigeria with a group of pregnant women [50]. The Generalized Anxiety Disorder-7 score is calculated by assigning scores of 0, 1, 2, and 3, to the response categories of ‘not at all’, ‘several days’, ‘more than half the days’, and ‘nearly every day’, respectively. Scores were categorized into 0–4 = normal anxiety, 5–9 = mild anxiety, 10–14 = moderate anxiety, and 15–21 = severe anxiety [47]. The categories of moderate and severe general anxiety were combined because of the small number of participants with severe general anxiety (6 persons). The Cronbach alpha score of this scale for this study was 0.92.

Parenting stress

Six items from the 19-item Parenting Stress Index used in the Detroit Dental Health Project [29] were used to measure maternal stress. The Parenting Stress Index has very good to excellent internal consistency [51] and was validated for use in the Nigerian population [52]. Possible scores for each item on the index ranged from 5 = almost always, to 4 = often, 3 = sometimes, 2 = rarely, to 1 = never. Higher scores reflect more frequent experiences of stress. Scores below the 81st percentile were categorized as normal stress range; 81st to 84th percentile scores indicated borderline stress, while scores equal to and greater than 85th percentile were classified as having clinically significant levels of stress. These reference percentile levels were proposed by Abidin and Staff [53]. The Cronbach alpha score of this scale for this study was 0.89.

Depressive symptoms

The 20-item Centre for Epidemiologic Studies and Depression Scale, developed by Radloff [54] and validated for use in Nigeria [55], was used to determine the level of depressive symptoms. Each item in the scale was assigned scores of 0–3, depending on the frequency of symptoms per week, with the total score ranging from 0 to 60. Scores of less than 15 indicated no depressive symptoms; 15–21 mild to moderate depressive symptoms; and 21–60 major depressive symptoms. The Cronbach alpha score of this scale for this study was 0.90.

Decision-making status

Information on maternal decision-making ability, measured using the demographic health survey instrument [56], was based on responses to three questions: the person who usually makes decisions on her healthcare, the person who usually decides on large household purchases, and the person who usually decides on visits to family or relatives, was retrieved. The responses included: mother only, husband/ partner only, mother and husband/ partner.

Confounding variables

Data retrieved included mother’s age at last birthday, which was categorized into three groups: 29 years, 30–39 years, 40 years and over. Information on mothers’ educational status (no formal education, primary school only, secondary school only or post-secondary school) and income were also retrieved. Income was defined as a monthly salary for persons in paid employment and categorized using the national Nigerian currency and wage into four categories: ≤N18,000 ($49)/month, N18,001- N30,000 ($84)/month, N30,001-N60,000 ($168)/month, and > N60,000 ($168)/month [57]. These variables were identified as confounders because of their relationship with the child’s nutritional status and maternal mental health status [58,59,60]. Other confounding variables were the children’s age at last birthday and the sex of the children at birth. The sociodemographic profile of the study participants has been reported in prior studies [43, 61,62,63,64].

Standardization of examiners

Five examiners were trained to obtain measurements that were not significantly different from that of a consultant nutritionist who was considered the “gold standard.” The consistency in measurement between the trainees and the expert was assessed using inter-examiner reliability scores. Twenty children were each measured for height and weight by the expert alongside the five examiners engaged in this study. The kappa scores for stunting, underweight, overweight and normal were 0.89, 0.92, 0.95 and 0.90 respectively.

Data Analysis

Descriptive analysis was conducted to determine the proportion of children recruited by each sociodemographic variable (age and sex), malnutrition status (underweight and overweight, stunting and thinness) and maternal decision-making status and the mental health status (levels of general anxiety, depressive symptoms, parental stress). We used multiple indictors of mental health to capture problems the individual may suffer from whether related (parental stress) or not related (general anxiety and depressive symptoms) to parenthood.

Four multivariable adjusted binary logistic regression models were developed, one for each type of malnutrition condition (underweight and overweight, stunted and thinness), with each having yes/ no responses. We used these various categories to comprehensively assess the factors associated with different types of malnutrition rather than focus on one category/ problem only in view of the extent of the problem in the country. Also, some children had more than one problem. We checked for multicollinearity in the models and dropped some variables that were correlated (r ≥ 0.5) with others from the models. We dropped off “autonomous decisions about household purchases” and “autonomous decisions about visits to family and relatives” because they were correlated with “autonomous decisions about access to health care”. Also, we dropped “maternal general anxiety” in the models that determined variables associated with underweight and thinness because it correlated with “maternal depressive symptoms” in those models. The estimated coefficients, expressed as adjusted odds ratios (AORs) and their 95% confidence intervals, were calculated. The analysis used a robust variance estimator to allow for direct estimation of the ORs. The statistical analyses were conducted with Intercooled STATA (release 15) for windows. Statistical significance was inferred at p  0.05.

Ethics approval

Ethical approval for the study was obtained from the Obafemi Awolowo University Teaching Hospitals Complex Health Research Ethics Committee (NHREC/27/01/2009a and IRB/EC/0004553). Written informed consent was provided by the mothers and mothers on behalf of their children in the primary study.

Results

Only 493 (31.8%) of the study participants had normal nutritional status. Others were thin (30.8%), stunted (26.8%), underweight (23.3%) and overweight/obese (11.3%). There were 68 (4.4%) mothers with moderate to severe general anxiety levels, 329 (21.2%) mothers with a clinically significant level of parenting stress and 374 (24.2%) mothers with mild to severe depressive symptoms. The majority of mothers were capable of autonomous decisions regarding access to health care (72.8%), household purchases (77.8%) and visits to family and relatives (76.6%).

Table 1 highlights the maternal mental health status and decision-making status associated with the nutritional status of the child. Maternal general anxiety and depressive symptoms were not significantly associated with the child being underweight, overweight/obese, stunted, thin or normal. The proportion of children with mothers reporting normal parental stress levels who were underweight (p = 0.009) and overweight/obese (p = 0.042) were significantly higher than mothers with borderline or clinically significant parental stress.

Table 1 Bivariate Analysis of the association between child-mother pairs’ characteristics and nutritional status of children younger than 6 years resident in Ile-Ife, Nigeria (N = 1549)*

In addition, maternal decision-making status was associated with being stunted, thin and normal nutritional status. A higher proportion of children with mothers able to make decisions on visits to family/relatives were stunted compared to children of mothers unable to make this decision autonomously (p = 0.014). A higher proportion of children with mothers able to decide on access to health care (p < 0.001), household purchase (p = 0.002) and visits to family/relatives (p < 0.001) were thin compared to children of mothers unable to make those decisions autonomously. Also, a higher proportion of children with mothers who can make decisions about access to health care (p = 0.001), and visits to family/relatives (p = 0.016) had normal weight compared with children of mothers who could not make those decisions autonomously.

Table 2 shows the outcome of the multivariable logistic regression analysis, determining the association between maternal mental health and decision-making status and children’s nutritional status.

Table 2 Multivariable logistic regression analysis of maternal psychosocial and economic factors associated with malnutrition among children younger than 6 years resident in Ile-Ife, Nigeria (N = 1549)

Variables associated with children being underweight

Mothers with clinically significant parenting stress levels were less likely to have children who were underweight (AOR 0.75; 95% CI: 0.58—0.98; p = 0.033) than children of mothers who had normal parenting stress. Also, children of mothers who had severe depressive symptoms were less likely to be underweight than children of mothers with normal depressive symptoms (AOR 0.70; 95% CI: 0.50—0.98; p = 0.041). Mothers with a substitute decision maker on access to health care were less likely to have children who were underweight compared with children of mothers who made autonomous decisions on access to health care (AOR 0.79; 95% CI: 0.63—0.98; p = 0.035).

Variables associated with children being overweight/obese

There was no independent variable associated with overweight/obese.

Variables associated with children being stunted

The only maternal explanatory variable associated with children being stunted was general anxiety. Mothers with mild general anxiety were less likely to have children who were stunted than mothers with normal general anxiety (AOR 0.72; 95% CI: 0.53, 0.98; p = 0.034).

Variables associated with children being thin

The only maternal explanatory variable associated with children being thin was maternal decision-making status. Mothers with someone else making their health access decision were less likely to have children who were thin than those who made the decisions themselves (AOR: 0.65; 95% CI: 0.53—0.80; p < 0.001).

Discussion

The study results suggest a complex relationship between maternal psychosocial factors and the nutritional status of children. The maternal variables associated with child malnutrition in this study population were mild general anxiety, clinically significant parenting stress and severe depressive symptoms. Mothers with mild general anxiety seem less likely to have children who were stunted; while mothers with severe depressive symptoms and clinically significant parenting stress seem less likely to have underweight children. Similarly, mothers for whom someone else decides on access to health care were less likely to have children who were underweight and thin. Our study hypotheses were therefore supported by the study findings although the directions of the associations raise more questions than they provide answers.

One of this study strengths was the inclusion of multiple potential risk factors in the study model, thereby increasing the possibility of simulating real-life risk exposure. However, the low R2 of the models studied indicate that variables in the models did not account for most of the variations in children’s nutritional status. Some confounding and mediating factors - the child’s birth weight and household food insecurity, child’s physical health, breastfeeding status [12] and parental Body Mass Index (BMI) [65] - were not included in the regression analysis as these were not collected in the primary dataset. Childhood illness is also a risk factor for growth failure [66] and was not included. The primary study excluded children who were on prolonged use of sweetened medication, which implied the exclusion of children with chronic illnesses; this exclusion helped reduce some confounders for this study. Also, this was a cross sectional study and so we are unable to determine a causal relationship between the variables. In addition, the data excluded details of children younger than 6 months old since the primary data was collected for children who should have erupted teeth. Our study findings are therefore not applicable to neonates and young infants. Despite these limitations, this study was able to demonstrate that some maternal psychosocial factors played a significant role in children’s nutritional status in the study setting.

Interestingly, mothers with severe depressive symptoms and clinically significant parenting stress seem less likely to have children who were underweight. We postulate that in the study environment, mothers derive some form of social capital from their social networks and ties to other individuals, groups, and the larger community [67, 68]. For a community-based society like Nigeria where communal living and access to community support is high [69], individuals with mental health problems have increased social support which may improve the health and wellbeing of the child [70]. In Nigeria, where the number of trained mental health professionals is few and access to social service is poor, families often play a prominent role in managing mental health disorders [71]. These social ties may ameliorate the impact of maternal mental health problems on the nutritional health of the child. Prior studies conducted in developing countries reported an association between maternal depressive symptoms and the child being underweight [72,73,74,75]. No association was found between these two variables in Brazil [76]. Other studies also found an association between maternal depression and the child being stunted [72, 73], which we did not find in our study. Future studies are needed to explore and identify if there are cultural nuances that moderate or mediate the association between maternal depression and nutritional status of children.

The study also showed that maternal decision-making ability about access to health care affected children’s nutritional status negatively: having someone else – likely the husband in a patriarchal society like Nigeria [77] - take decisions about healthcare access reduces the risk of being underweight and thin. These findings may reflect a societal context wherein male spouses are often better educated about health issues and wealthier and are better placed to make the needed out-of-pocket expense for health care [78, 79]. In effect, women may be able to facilitate access of the child to health care when they receive funds from significant others.

On the contrary, women who can make independent decisions about access to health care, are likely to be working mothers. Health care is often paid for through out-of-pocket expenses in Nigeria, and thus, managing childcare health needs require some level of financial independence [79]. Working mothers, however, have less time to pay attention to the nutritional needs of their young children since they resume back to work shortly after the birth of the child [80,81,82,83]. Paid maternity leave can improve children’s nutritional health and is an important s policy tool because it may enable many maternal practices that can improve the nutritional status of the child [84, 85]. The study findings and our postulations need to be further tested, and reasons proffered for the association between the reduced odds for wasting when mothers can make autonomous decisions about a visit to family/relatives.

We also observed that mild general anxiety was protective from stunting. Mild anxiety may enable mothers to react more sensitively to the health needs of their children including the need for nutritional care. A prior study had demonstrated that maternal anxiety was associated with child obesity [86]. This may be because anxiety is associated with maternal overstimulation [87], which then results in forceful feeding of the child [88]. High anxiety level on the contrary, may be counterproductive and result in low diet quality for the child [89].

Our findings have contributed to highlighting the complexity of the interactions between maternal psychosocial factors, children’s nutritional status and the country of origin of the study. When we compared our findings with those of other studies, we observed disparities in findings for different countries. This points to the likelihood of social context being a possible mediating factor in the relationship between maternal psychosocial factors and children’s nutritional status. If confirmed, countries will need to understand how these factors are associated, and how other factors mediate or moderate their relationships.

For Nigeria, the findings indicate that the level of general anxiety, parenting stress, depressive symptoms, and decision-making status of mothers should be given due consideration in the design and implementation of nutrition programs for children younger than 6 years. Broadening obesity prevention efforts to include a reduction in maternal depression burden may be an important nutrition implementation guideline in the study setting [90]. Also, a perinatal assessment for depression and general anxiety status may likely reduce the risk for children’s growth failure. Access to counselling interventions that draw on techniques from cognitive-behavioral therapy and problem-solving therapy, provided within a supportive group can help rebuild a sense of agency by promoting self-efficacy for mothers with psychosocial challenges [91].

Conclusion

Mothers in Ile-Ife, Nigeria with mild general anxiety, clinically significant parenting stress, severe depressive symptoms, and less decision-making autonomy regarding access to healthcare, seem less likely to have children younger than 6 years with a form of malnutrition. These results seem counterintuitive though the socio-cultural context of the study location may explain the findings. The study results seem to suggest that relationships between maternal psychosocial status and children’s nutritional status may be moderated by sociocultural context. Further studies are needed to understand how sociocultural factors may moderate maternal psychosocial status and children’s nutritional status as this can inform the design of malnutrition programs for children.

Data Availability

All data generated for this study are presented in the manuscript. The dataset for the online study data can however be accessible on reasonable request from one the study author, Morenike Oluwatoyin Folayan, toyinukpong@yahoo.co.uk.

Abbreviations

AOR:

Adjusted Odds Ratio

BMI:

Body Mass Index

CI:

Confidence Interval

SD:

Standard Deviation

WHO:

World Health Organization

References

  1. Patel V, Rahman A, Jacob KS, et al. Effects of maternal mental health of infant growth in low-income countries: new evidence from South Asia. BMJ. 2004;328:820–3.

    Article  PubMed  PubMed Central  Google Scholar 

  2. Patel V, Rodrigues M, De Souza N. Gender, poverty and post-natal depression: a cohort study from Goa, India. Am J Psychiatry. 2002;159:43–7.

    Article  PubMed  Google Scholar 

  3. Chandran M, Tharyan P, Muliyil J, et al. Post-partum depression in a cohort of women from a rural area of Tamil Nadu, India. Incidence and risk factors. Br J Psychiatry. 2002;181:499–504.

    Article  PubMed  Google Scholar 

  4. Harpham T, Huttly S, De Silva MJ, Abramsky T. Maternal mental health and child nutritional status in four developing countries. J Epidemiol Community Health. 2005;59(12):1060–4.

    Article  PubMed  PubMed Central  Google Scholar 

  5. Dib EP, Padovani FHP, Perosa GB. Mother-child interaction: implications of chronic maternal anxiety and depression. Psicol Refl Crít. 2019;32:10.

    Article  Google Scholar 

  6. Anoop S, Saravanan B, Joseph A, Cherian A, Jacob K. Maternal depression and low maternal intelligence as risk factors for malnutrition in children: a community based case–control study from South India. Arch Dis Child. 2004;89(4):325–9.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  7. Montgomery SM, Bartley MJ, Wilkinson RG. Family conflict and slow growth. Arch Dis Child. 1997;77:326–30.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  8. Kaitz M, Maytal HR, Devor N, Bergman L, Mankuta D. Maternal anxiety, mother-infant interactions, and infants’ response to challenge. Infant Behav Dev. 2010;33(2):136–48.

    Article  PubMed  Google Scholar 

  9. Feldman R, Granat A, Pariente C, Kanety H, Kuint J, Gilboa-Schechtman E. Maternal depression and anxiety across the postpartum year and infant social engagement, fear regulation, and stress reactivity. J Am Acad Child Adolesc Psychiatry. 2009;48(9):919–27.

    Article  PubMed  Google Scholar 

  10. Daniels LA. Feeding Practices and parenting: a pathway to Child Health and Family Happiness. Ann Nutr Metab. 2019;74(Suppl 2):29–42.

    Article  CAS  PubMed  Google Scholar 

  11. Owoaje E, Onifade O, Desmennu A. Family and socioeconomic risk factors for undernutrition among children aged 6 to 23 months in Ibadan, Nigeria. Pan Afr Med J. 2014;17:161.

    Article  PubMed  PubMed Central  Google Scholar 

  12. Rahman MM, Saima U, Goni MA. Impact of maternal Household decision-making autonomy on Child Nutritional Status in Bangladesh. Asia Pac J Public Health. 2015;27(5):509–20.

    Article  PubMed  Google Scholar 

  13. Fadare O, Amare M, Mavrotas G, Akerele D, Ogunniyi A. Correction: Mother’s nutrition-related knowledge and child nutrition outcomes: empirical evidence from Nigeria. PLoS ONE. 2019;14(4):e0215110.

    Article  PubMed  PubMed Central  Google Scholar 

  14. Fadare O, Amare M, Mavrotas G, Akerele D, Ogunniyi A. Mother’s nutrition-related knowledge and child nutrition outcomes: empirical evidence from Nigeria. PLoS ONE. 2019;14(2):e0212775.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  15. Wu J, Xiao J, Li T, Li X, Sun H, Chow EP, Lu Y, Tian T, Li X, Wang Q, Zhuang X. A cross-sectional survey on the health status and the health-related quality of life of the elderly after flood disaster in Bazhong city, Sichuan, China. BMC Public Health. 2015;15(1):163.

    Article  PubMed  PubMed Central  Google Scholar 

  16. Finlay JE, Özaltin E, Canning D. The association of maternal age with infant mortality, child anthropometric failure, diarrhoea and anaemia for first births: evidence from 55 low-and middle-income countries. BMJ open. 2011;1(2).

  17. Oyelohunnu MA, Oshodi YO, Campbell EA, Eigbike M, Odeyemi KA. Impact of maternal mental health on maternal-child interaction in attendees in a community health clinic in Lagos, Nigeria. J Clin Sci. 2016;13:105–11.

    Article  Google Scholar 

  18. Bandura A. Health promotion from the perspective of social cognitive theory. Psychol Health. 1998;13(4):623–49.

    Article  Google Scholar 

  19. Finlayson TL. Mothers’ self-efficacy and oral health in low-income african american children in Detroit. University of Michigan; 2005.

  20. Haithar S, Kuria MW, Sheikh A, Kumar M, Vander Stoep A. Maternal depression and child severe acute malnutrition: a case-control study from Kenya. BMC Pediatr. 2018;18(1):289.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  21. Barnett B, Schaafsma MF, Guzman AM, Parker GB. Maternal anxiety: a 5-year review of an intervention study. J Child Psychol Psychiatry. 1991;32(3):423–38.

    Article  CAS  PubMed  Google Scholar 

  22. O’Brien LM, Heycock EG, Hanna M, Jones PW, Cox JL. Postnatal depression and faltering growth: a community study. Pediatrics. 2004;113(5):1242–7.

    Article  PubMed  Google Scholar 

  23. Adewuya AO, Ola B, Aloba OO, Dada AO, Fasoto OO. Prevalence and correlates of depression in late pregnancy among nigerian women. Depress Anxiety. 2007;24(1):15–21.

    Article  PubMed  Google Scholar 

  24. Adewuya AO, Ola BA, Aloba OO, Mapayi BM. Anxiety disorders among nigerian women in late pregnancy: a controlled study. Arch Women Ment Health. 2006;9(6):325–8.

    Article  CAS  Google Scholar 

  25. National Population Commission (NPC). [Nigeria] and ICF. Nigeria Demographic and Health Survey 2018. Nigeria, and Rockville, Maryland, USA: NPC and ICF.: Abuja; 2019.

    Google Scholar 

  26. National Bureau of Statistic. Report on the nutrition and health situation of Nigeria. 2018. Accessible from: https://www.unicef.org/nigeria/media/2181/file/Nigeria-NNHS-2018.pdf. Accessed 12 December 2019.

  27. UNICEF., Nigeria. Nutrition [no date]. Accessible from: https://www.unicef.org/nigeria/nutrition. Accessed 24 December, 2019.

  28. Myatt M, Khara T, Schoenbuchner S, Pietzsch S, Dolan C, Lelijveld N, Briend A. Children who are both wasted and stunted are also underweight and have a high risk of death: a descriptive epidemiology of multiple anthropometric deficits using data from 51 countries. Arch Public Health 2018 Jul 16;76:28. doi: https://doi.org/10.1186/s13690-018-0277-1.

  29. Pi-Sunyer X. The medical risks of obesity. Postgrad Med. 2009 Nov;121(6):21–33. https://doi.org/10.3810/pgm.2009.11.2074.

  30. Santoso MV, Kerr RB, Hoddinott J, Garigipati P, Olmos S, Young SL. Role of women’s empowerment in child nutrition outcomes: a systematic review. Adv Nutr 2019 Nov 1;10(6):1138–51.

  31. Salman KK, Salawu MB, Oni OA, Obi-Egbedi O. Does maternal autonomy influence child Nutrition in Rural Nigeria? J Hunger Environ Nutr. 2020; 1–20.

  32. Agu N, Emechebe N, Yusuf K, Falope O, Kirby RS. Predictors of early childhood undernutrition in Nigeria: the role of maternal autonomy. Public Health Nutr. 2019;22(12):2279–89.

    Article  PubMed  Google Scholar 

  33. Thorpe S, VanderEnde K, Peters C, Bardin L, Yount KM. The influence of women’s empowerment on child immunization coverage in low, lower-middle, and upper-middle income countries: a systematic review of the literature. Matern Child Health J. 2015;20(1):172–86.

    Article  Google Scholar 

  34. Hurt L, Paranjothy S, Lucas PJ, Watson D, Mann M, Griffiths LJ, Lingam R. Interventions that enhance health services for parents and infants to improve child development and social and emotional well-being in high-income countries: a systematic review. BMJ Open. 2018;8(2):e014899.

    Article  PubMed  PubMed Central  Google Scholar 

  35. Vuorenmaa M, Halme N, Perälä ML, Kaunonen M, Åstedt-Kurki P. Perceived influence, decision‐making and access to information in family services as factors of parental empowerment: a cross‐sectional study of parents with young children. Scand J Caring Sci. 2016;30(2):290–302.

    Article  PubMed  Google Scholar 

  36. Heckert J, Olney DK, Ruel MT. Is women’s empowerment a pathway to improving child nutrition outcomes in a nutrition-sensitive agriculture program?: evidence from a randomized controlled trial in Burkina Faso. Soc Sci Med. 2019;233:93–102.

    Article  PubMed  PubMed Central  Google Scholar 

  37. Santos DS, Santos DN, Silva Rde C, Hasselmann MH, Barreto ML. Maternal common mental disorders and malnutrition in children: a case-control study. Soc Psychiatry Psychiatr Epidemiol. 2011;46(7):543–8.

    Article  PubMed  Google Scholar 

  38. Nguyen PH, Saha KK, Ali D, Menon P, Manohar S, Mai LT, et al. Maternal mental health is associated with child undernutrition and illness in Bangladesh, Vietnam and Ethiopia. Public Health Nutr. 2014;17(6):1318–27.

    Article  PubMed  Google Scholar 

  39. Abdullahi AT, Farouk ZL, Imam A. Common mental disorders in mothers of children attending out-patient malnutrition clinics in rural north-western Nigeria: a cross-sectional study. BMC Public Health. 2021;21:185. https://doi.org/10.1186/s12889-021-10227-8.

    Article  PubMed  PubMed Central  Google Scholar 

  40. Ojagbemi A, Gureje O. Sociocultural contexts of mental illness experience among Africans. Transcult Psychiatry. 2021;58(4):455–9. https://doi.org/10.1177/13634615211029055.

    Article  PubMed  Google Scholar 

  41. White D, Dynes M, Rubardt M, Sissoko K, Stephenson R. The influence of intrafamilial power on maternal health care in Mali: perspectives of women, men and mothers-in-law. Int Perspect Sex Reprod Health. 2013;39(2):58–68. https://doi.org/10.1363/3905813.

    Article  PubMed  Google Scholar 

  42. Umallawala T, Puwar T, Pandya A et al. (July 27, 2022) Sociocultural Determinants of Nutritional Status Among Children Under Five Years of Age: An Ethnographic Study From Gujarat. Cureus 14(7): e27377. doi:https://doi.org/10.7759/cureus.27377.

  43. Folayan MO, Alade M, Adeniyi A, El Tantawi M, Finlayson TL. Association between developmental dental anomalies, early childhood caries and oral hygiene status of 3-5-year-old children in Ile-Ife, Nigeria. BMC Oral Health. 2019;20(1):1.

    Article  PubMed  PubMed Central  Google Scholar 

  44. Newsom JT. Psy 522/622 Multiple Regression and Multivariate Quantitative Methods, Winter 2021. Available at: http://web.pdx.edu/~newsomj/mvclass/ho_sample%20size.pdf. Accessed: 11 June 2021.

  45. De Onis M, Onyango AW, Borghi E, et al. Comparison of the World Health Organization (WHO) child growth Standards and the National Center for Health Statistics/WHO international growth reference: implications for child health programmes. Public Health Nutr. 2006;9(7):942–7.

    Article  PubMed  Google Scholar 

  46. World Health Organisation. Measuring a child’s growth. 2008. Available at: www.who.int/childgrowth/training/measuring_growth.pdf. Accessed: 10 September 2017.

  47. Casadei K, Kiel J. Anthropometric measurement. StatPearls [Internet]. Treasure Island (FL): StatPearls Publishing; 2020.

    Google Scholar 

  48. World Health Organization Obesity and overweight. 9 June 2021. Available at: https://www.who.int/news-room/fact-sheets/detail/obesity-and-overweight#:~:text=Overweight%20and%20obesity%20are%20defined%20as%20follows%20for%20children%20aged,the%20WHO%20Growth%20Reference%20median/. Accessed: 11 June 2021.

  49. Swinson RP. The GAD-7 scale was accurate for diagnosing. Evid Based Med. 2006;11(6):184.

    Article  PubMed  Google Scholar 

  50. Adewuya A, Ola B, Aloba O, Mapayi B. Anxiety disorders among nigerian women in late pregnancy: a controlled study. Arch Women Ment Health. 2006;9(6):325–8.

    Article  CAS  Google Scholar 

  51. Reitman D, Currier RO, Stickle TR. A critical evaluation of the parenting stress index-short form (PSI-SF) in a head start population. J Clin Child Adolesc Psychol. 2002;31(3):384–92.

    Article  PubMed  Google Scholar 

  52. Alade M. Maternal psychosocial factors and oral health behaviours as risk indicators for early childhood caries in preschool children in Ile-Ife. Dissertation submitted for the award of the Fellowship of the West Africa Postgraduate College. 2020.

  53. Abidin RR, Staff AP. Parenting Stress Index- Short Form Computer Assisted Screening Report. 2010:1–4. Available at: www4.parinc.com/webuploads/samplerpts/psi_short_form.pdf. Accessed 27 August 2020.

  54. Radloff LS. The CES-D scale: a self-report depression scale for research in the general population. Appl Psychol Meas. 1977;1(3):385–401.

    Article  Google Scholar 

  55. Shaeer K, Osegbe D, Siddiqui S, et al. Prevalence of erectile dysfunction and its correlates among men attending primary care clinics in three countries: Pakistan, Egypt, and Nigeria. Int J Impot Res. 2003;15:8–S14.

    Article  Google Scholar 

  56. The DHS Program. DHS Model Questions. [No date]. Available at: https://dhsprogram.com/What-We-Do/Survey-Types/DHS-Questionnaires.cfm#CP_JUMP_16179. Accessed: 24 December 2019.

  57. Agburu JI. Recent trends in wage and salary administration in Nigeria: a synopsis in theoretical and empirical challenge. Int J Basis Appl Sci. 2012;1(2):257–68.

    Google Scholar 

  58. Muraca GM, Joseph KS. The association between maternal age and depression. J Obstet Gynecol Can. 2014;36(9):803–10.

    Article  Google Scholar 

  59. Augustine JM, Crosnoe R. Mothers’ depression and educational attainment and their children’s academic trajectories. J Health Soc Behav. 2010;51(3):274–90.

    Article  PubMed  PubMed Central  Google Scholar 

  60. Patel V, Rodrigues M, DeSouza N. Gender, poverty, and postnatal depression: a study of mothers in Goa, India. Am J Psychiatry. 2002;159(1):43–7.

    Article  PubMed  Google Scholar 

  61. Folayan MO, El Tantawi M, Oginni AB, Alade M, Adeniyi A, Finlayson TL. Malnutrition, enamel defects, and early childhood caries in preschool children in a sub-urban Nigeria population. PLoS ONE. 2020;15(7):e0232998. https://doi.org/10.1371/journal.pone.0232998.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  62. Folayan MO, El Tantawi M, Oginni A, Adeniyi A, Alade M, Finlayson TL. Psychosocial, education, economic factors, decision-making ability, and caries status of mothers of children younger than 6 years in suburban Nigeria. BMC Oral Health. 2020;20(1):131. https://doi.org/10.1186/s12903-020-01120-8.

    Article  PubMed  PubMed Central  Google Scholar 

  63. Alade M, Folayan MO, El Tantawi M, Oginni AB, Adeniyi AA, Finlayson TL. Early childhood caries: are maternal psychosocial factors, decision-making ability, and caries status risk indicators for children in a sub-urban nigerian population? BMC Oral Health. 2021;21(1):73. https://doi.org/10.1186/s12903-020-01324-y.

    Article  PubMed  PubMed Central  Google Scholar 

  64. Folayan MO, Alade M, Adeniyi A, El Tantawi M, Finlayson TL. Association between maternal socioeconomic factors, decision-making status, and dental utilization by children with early childhood caries in sub-urban Nigeria. J Public Health Dent. 2020;80(4):288–96. https://doi.org/10.1111/jphd.12383.

    Article  PubMed  Google Scholar 

  65. Tang D, Bu T, Dong X. Are parental dietary patterns associated with children’s overweight and obesity in China? BMC Pediatr. 2020;20(1):1–1.

    Article  Google Scholar 

  66. Malinauskas BM, Gropper SS, Kawchak DA, Zemel BS, Ohene-Frempong K, Stallings VA. Impact of acute illness on nutritional status of infants and young children with sickle cell disease. J Am Diet Assoc. 2000;100(3):330–4.

    Article  CAS  PubMed  Google Scholar 

  67. Reblin M, Uchino BN. Social and emotional support and its implication for health. Curr Opin Psychiatry. 2008;21(2):201.

    Article  PubMed  PubMed Central  Google Scholar 

  68. Mittelmark MB. Social ties and health promotion: suggestions for population-based research. Oxford University Press; 1999.

  69. Folayan MO, Haire B. Communitarian societies and public engagement in public health. 2017; 27(1): 6–13.

  70. Lee LC, Halpern CT, Hertz-Picciotto I, Martin SL, Suchindran CM. Childcare and social support modify the association between maternal depressive symptoms and early childhood behaviour problems: a US national study. J Epidemiol Community Health. 2006;60(4):305–10.

    Article  PubMed  PubMed Central  Google Scholar 

  71. Alem A, Jacobsson L, Hanlon C. Community-based mental health care in Africa: mental health workers’ views. World Psychiatry. 2008;7(1):54.

    Article  PubMed  PubMed Central  Google Scholar 

  72. Saeed Q, Shah N, Inam S, Shafique K. Maternal depressive symptoms and child nutritional status: a cross-sectional study in socially disadvantaged pakistani community. J Child Health Care. 2017;21(3):331–42.

    Article  PubMed  Google Scholar 

  73. Surkan PJ, Kennedy CE, Hurley KM, Black MM. Maternal depression and early childhood growth in developing countries: systematic review and meta-analysis. Bull World Health Organ. 2011;89:607–15.

    Article  PubMed Central  Google Scholar 

  74. Lampard AM, Franckle RL, Davison KK. Maternal depression and childhood obesity: a systematic review. Prev Med. 2014;59:60–7.

    Article  PubMed  Google Scholar 

  75. Wang L, Anderson JL, Dalton WT III, Wu T, Liu X, Zheng S, Liu X. Maternal depressive symptoms and the risk of overweight in their children. Matern Child Health J. 2013;17(5):940–8.

    Article  PubMed  Google Scholar 

  76. Surkan PJ, Ryan LM, Vieira LM, Berkman LF, Peterson KE. Maternal social and pyschological conditions and physical growth in low-income children in Piaui, Northeast Brazil. Soc Sci Med. 2007;64(2):375–88.

    Article  PubMed  Google Scholar 

  77. Brown CK. Gender roles and household allocation of resources and decision-making in Ghana. The changing family in Ghana. 1996:21–41.

  78. Makama GA. Patriarchy and gender inequality in Nigeria: the way forward. Eur Sci J. 2013;9(17).

  79. Aregbeshola BS, Khan SM. Out-of-pocket payments, catastrophic health expenditure and poverty among households in Nigeria 2010. Int J Health Policy Manag. 2018;7(9):798–806.

    Article  PubMed  PubMed Central  Google Scholar 

  80. Popkin BM, Solon E. Income. Time, the working mother and child nutriture. Environ Child Health. 1976;22(4):156–66.

    Google Scholar 

  81. Blau DM. Investment in child nutrition and women’s allocation of time in developing countries. Discussion Paper no. 371. New Haven. Conn. USA: Economic Growth Center, Yale University, 1980. 16. Hart G. Women’s participation in the labor force: implications for employment and health nutrition programs. Ithaca. NY, USA: Cornell University Press. 1975.

  82. Popkin BM, Bisgrove EZ, Gopaldas T, Patel P, Bakshi M. Selected socioeconomic, environmental, maternal, and child factors associated with the nutritional status of infants and toddlers. Food Nutr Bull 1988;10(4):29–34.

  83. Abbi R, Christian P, Gujral S, Gopaldas T. The impact of maternal work status on the nutrition and health status of children. FoodNutr Bull. 1991;13(1):1–6.

    Google Scholar 

  84. Ruel MT, Alderman H, Maternal and Child Nutrition Study Group. Nutrition-sensitive interventions and programmes: how can they help to accelerate progress in improving maternal and child nutrition? Lancet. 2013;382:536–51.

    Article  PubMed  Google Scholar 

  85. Jahagirdar D, Harper S, Heymann J, Swaminathan H, Mukherji A, Nandi A. The effect of paid maternity leave on early childhood growth in low-income and middle-income countries. BMJ Glob Health. 2017 Sep 7;2(3): e000294. doi: https://doi.org/10.1136/bmjgh-2017-000294.

  86. Nawa N, Black MM, Araya R, Richiardi L, Surkan PJ. Pre- and post-natal maternal anxiety and early childhood weight gain. J Affect Disord. 2019;257:136–42. https://doi.org/10.1016/j.jad.2019.06.068.

    Article  PubMed  Google Scholar 

  87. Kaitz M, Maytal H. Interactions between anxious mothers and their infants: an integration of theory and research findings. Infant Ment Health J. 2005 Nov;26(6):570–97. https://doi.org/10.1002/imhj.20069.

  88. Farrow CV, Blissett JM. Is maternal psychopathology related to obesigenic feeding practices at 1 year? Obes Res. 2005 Nov;13(11):1999–2005. https://doi.org/10.1038/oby.2005.245.

  89. Trude ACB, Black MM, Surkan PJ, Hurley KM, Wang Y. Maternal anxiety and diet quality among mothers and toddlers from low-income households. Matern Child Nutr 2020 Oct;16(4):e12992. doi: https://doi.org/10.1111/mcn.12992.

  90. Donkoh SA, Alhassan H, Nkegbe PK. Food expenditure and household welfare in Ghana. Afr J Food Sci. 2014;8:164–75.

    Article  Google Scholar 

  91. Chibanda D, Mesu P, Kajawu L, Cowan F, Araya R, Abas MA. Problem-solving therapy for depression and common mental disorders in Zimbabwe: piloting a task-shifting primary mental health care intervention in a population with a high prevalence of people living with HIV. BMC Public Health. 2011;11:82.

    Article  Google Scholar 

Download references

Acknowledgements

We acknowledge and thank the study participants for the contributions they made to generating new knowledge.

Funding

The study was self-funded.

Author information

Authors and Affiliations

Authors

Contributions

MOF conceptualized and developed the study protocol. MOF and MA organized the data collection. ABO conducted the initial analyses. MOF drafted the initial manuscript. MET, AA, MA, TLF and ABO reviewed and revised the manuscript for important intellectual content. All authors read and approved the final manuscript.

Corresponding author

Correspondence to Morenike Oluwatoyin Folayan.

Ethics declarations

Ethics approval and consent to participate

Ethical approval for the study was obtained from the Obafemi Awolowo University Teaching Hospitals Complex Health Research Ethics Committee (NHREC/27/01/2009a and IRB/EC/0004553). Written informed consent was obtained provided by the all mothers and mothers on behalf of all children who participated in the primary study. All the procedures were followed in accordance with the national guidelines on research ethics and the Declaration of Helsinki.

Consent for publication

Not applicable.

Competing interests

Morenike Oluwatoyin Folayan and Maha El Tantawi are senior editorial consultant with BMC Oral Health. All other authors declare no conflict of interest.

Additional information

Publisher’s Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data.

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Folayan, M.O., Oginni, A.B., El Tantawi, M. et al. Association between maternal decision-making and mental health and the nutritional status of children under 6 years of age in sub-urban Nigeria. BMC Public Health 23, 1159 (2023). https://doi.org/10.1186/s12889-023-16055-2

Download citation

  • Received:

  • Accepted:

  • Published:

  • DOI: https://doi.org/10.1186/s12889-023-16055-2

Keywords