Association of maternal characteristics with child feeding indicators and nutritional status of children under-two years in Rural Ghana

Background: Optimal nutrition during the first two years of a child’s life is critical for the reduction of morbidity and mortality. In Ghana, majority of children miss out on optimal nutrition and only few (13%) of children receive a Minimum Acceptable Diet (MAD). Several studies have investigated the influence of community-level factors on infants and young children feeding (IYCF) practices. However, little is known about the influence of maternal factors on IYCF practices in rural settings. Therefore, this study assessed the influence of maternal factors on the feeding indicators and nutritional status of children aged 6–23 months in two administrative districts in Ghana. Methods: Data were collected among 935 mothers who had children aged 6–23 months and accessed 21 Child Welfare Clinics within the study area. The study involved a face- to-face interview using structured questionnaires to capture maternal characteristics, dietary intake and anthropometric measurements of children. Multivariate logistic regression was used to study the association between maternal factors and child nutrition outcomes (MAD, dietary diversity score (DDS) and anthropometric indicators) using Stata 16.0 software. Results: Being employed (AOR = 3.07, 95% CI: 1.71—5.49, p < 0.001) and attaining secondary or higher education (AOR = 2.86, 95% CI: 1.42—5.78, p = 0.003) were significant predictors of children receiving MAD. Similarly, having an average decision-making autonomy increased the child’s odds of receiving MAD (AOR = 1.68, 95% CI: 1.02—2.76, p = 0.040). Children of mothers who attained secondary or a higher level of education (AOR = 0.59, 95% CI: 0.36 -0.97, p = 0.040) and those whose mothers were employed (AOR = 0.71, 95% CI: 0.47—1.07, p = 0.043) were associated with a reduced risk of underweight and stunting respectively. Children of mothers with average financial independence status were more likely to receive diversified meals (AOR = 1.55, 95% CI: 1.01–2.38, p = 0.045). Conclusions: High educational level and being employed have positive influence on MAD, stunting and underweight of children. High decision-making power and average financial independence of mothers are good predictors of children receiving MAD. Family planning, women empowerment in decision-making, providing employment opportunities for mothers and promoting girl-child education are recommended. The study adopted a cross-sectional design in which quantitative data were collected. The Eastern Region of Ghana was selected for this study because, according to the GDHS (2015) report, only 4.3% of children residing in that region received a minimum acceptable diet compared to the national average of 13%. Specifically, this study was conducted in two districts − the Kwahu Afram Plains North District (KAPND) and the Kwahu Afram Plains South District (KAPSD) − which were ranked as the first and second districts with the highest prevalence of underweight children in the Eastern Region in both 2016 and 2017 (Eastern Region Health Directorate, 2016; 2017). The study participants included 935 mothers with their under-two-year-old children who were randomly selected from 21 randomly selected Child Welfare Clinics (CWCs) in the two districts. These mothers accessed the CWCs for growth monitoring and promotion services for their young children. Eligibility criteria for infants included healthy singleton infants with ages between 0 and 23 months, gestational ages between 37 and 42 weeks, birthweight between 2,500 and 4,000 g, and without metabolic or physical problems. The gestational age and birth weight of the children were considered because available evidence indicates that a short gestational age, pre-term/premature or low birthweight infants are at higher risk of growth and nutritional deficits during the first year of life [16, 17]. The eligibility criteria for prospective study participants were assessed by checking the child’s health record booklet with the assistance of the nurses in-charge at the CWCs. Specifically, information on each child’s birthweight, birth defects or medication conditions was obtained from the health record booklet and formed the basis for determining their eligibility to participate in the study. Children who were twins were excluded from this study since the evidence regarding the differences between their nutritional status and that of singletons is inconsistent [18]. In addition, children whose twin siblings died during labour or birth were not considered. A child was also excluded if he/she had a chronic or congenital illness or any medical condition that interfered with either feeding (e.g. cleft palate) or the taking of body measurements. The sample size required for the study was estimated using the prevalence of underweight among children under-five years for the Kwahu Afram Plains North and South Districts in 2016, which are 22.0% and 16.3% respectively (District Health Directorate Report, 2016). The prevalence of underweight was used because it is a composite indicator reflecting both chronic and acute malnutrition and therefore, related to both stunting and wasting. This ensured that all the three indices of nutritional status were captured. On the average, prevalence for both the North and South districts was 19.2%, and the minimum sample size was estimated using the formula: n=Z2*p*(1-p)/e2 where Z = confidence level, p = proportion of underweight children in the combined districts and e = precision [19]. With a confidence level of 95%, Z = 1.96, e = 2.8% and p = 10.8%, the minimum sample size estimated was 765 children. Making a provision of 20% contingencies, a sample size of 912 (rounded up to 950) infants and children aged between 6 and 23 months was estimated for this study. A two-stage sampling strategy was employed in this study. Firstly, a total number of 21 health facilities (constituting one-third of total health facilities) were randomly selected from a total of 63 health facilities within the two districts. Secondly, mothers and their children aged between 6 and 23 months were recruited from the 21 randomly selected health facilities for the study. The total number of infants and young children who visit the CWCs in the selected health facilities on a monthly basis was obtained. Based on this information, the study participants were randomly selected proportionally to obtain the sample size. Ethical approval and clearance for the study was granted by the Dodowa Health Research Centre’s (DHRC) Institutional Review Board (IRB) of the Ghana Health Service (Reference/Identification: DHRCIRB/04/02/18) and the IRB of the University of Cape Coast (Reference/Identification: UCCIRB/CHLS/2018/02). Permission to conduct the study was also obtained from the Regional Health Directorate, the two District Health Management Teams (DHMT) and the Directors of Health Services in the 21 health facilities which were selected for the study. Informed consent to participate in the study was obtained from all study participants and mothers consented on behalf of their children. The participants consented to participant in the study by either thumb-printing or signing an informed-consent form. To ensure data confidentiality, participants were assigned unique identifiers instead of names. All data collection methods were carried out in accordance with relevant ethical guidelines of the Ghana Health Service Ethical Review Committee and the University of Cape Coast Ethical Review Board. The regulations involved in the conduct of this research involving study participants also took into consideration the Helsinki Declaration. A structured questionnaire was used. The questionnaire solicited for information on socio-demographic characteristics of the mother such as marital status, parity, highest level of education attained, employment status and caregiver's autonomy (decision-making power and financial independence). In addition, information on background characteristics of the index child such as sex, age, birth order and birth weight were collected. Furthermore, information on each caregiver's feeding practices for the index child was obtained by administering a 24-h dietary recall and a seven-day food group frequency questionnaire (FGFQ). Anthropometric measurement was carried out to determine the nutritional status of the children by accessing for height-for-age z-score (HAZ), weight-for-age z-score (WAZ) and weight-for-height z-score (WHZ). The recumbent length of children who were unable to stand upright was measured using an infantometer (UNICEF model, item no. 0114500). The World Health Organization’s guidelines for taking weight and length/height in children were followed for all the anthropometric measurements [20]. Children’s heads were held vertically against the head plate with the back, body and legs straight and flat in the centre of the measuring board, the knees straightened, the heels and feet firmly positioned by the researcher vertically against the footplate. Both length and height measurements were taken to the nearest 0.1 cm. A beam balance scale was used to take their weights to the nearest 0.1 kg. All weighing scales were calibrated daily using certified standardized weight test loads of 10 kg and 25 kg by setting it to zero prior to taking weight measurements. It was ensured that all weights were measured with light clothing and no shoes. Both height and weight measurements were taken in duplicates and the average recorded. A single 24-h Dietary recall (24HDR) method and a seven-day food group frequency questionnaire (FFQ) were used to collect information on all foods (including school meals) and beverages consumed by the children. The mothers were asked to recall all the foods and drinks given to the child during the previous day and also the number of times that they fed their children the previous day. Information about the number of times (food group frequency) a child had eaten from a particular food group during the past seven days was collected using a food group frequency questionnaire. The seven food groups included grains/roots/tubers; legumes/nuts; dairy; flesh foods; eggs; vitamin A-rich fruits and vegetables; other fruits and vegetables [21]. Mothers were asked to recall the number of days in a week that children ate from each of the seven food groups. Data collected using the 24HDR was used to estimate the minimum dietary diversity score (MDD) of the children. A child was considered to have met the requirement of being fed on a minimum dietary diversity if he/she ate from at least four out of the seven food groups during the day or night preceding the survey. The number of times that children had been offered meals in the past 24 h was used to estimate the minimum meal feeding frequency (MFF) of the children. The minimum acceptable diet (MAD) was estimated using the minimum DDS and the MFF. The children were sub-divided into four groups (less than 6 months, 6–8 months, 9–11 months, and 12 months and above) during the analysis of the feeding practices data to represent the variations in feeding recommendations for their different age groups. The scoring system for the IYCF indicators were dependent on the age group of each child and the current WHO feeding recommendations for that particular age group. The WHO Anthro software (World Health Organization, 2011) was used to transform the weight and length/height of the infants into the growth indices -weight-for-age, weight-for-length and length-for-age z-scores. Infants with z-scores less than -2 standard deviations from the median reference length-for-age/ height-for-age, weight-for-height/weight-for-length and weight-for-age z-scores were classified as stunted, wasted and underweight, respectively. The WHO recommends that children aged between 6 and 23 months should be given foods from at least four food groups each day to meet their minimum dietary diversity score. On the basis of this recommendation, a child in any age group who was not fed from any food group or fed from only three or less food groups in a day earned a score of 0. A score of 1 was assigned to a child who was fed from four food groups, and a score of 2 was given to children in the age groups 6–8 months and 9–12 months if more than 4 food groups are consumed. The scoring system that was applied in the study was based on the scoring pattern for the feeding indicator of dietary diversity score as applied in previous studies [22, 23]. A child aged between 13 and 23 months was given a score of 3 if she consumed more than four food groups within a 24-h period before the caregiver is interviewed. This is because of WHO’s emphasis on feeding children above 12 months from a wide variety of foods and gradually substituting their usual infant foods with family foods. Meal feeding frequency (MFF) score refers to the number of times that a child consumes solid or semi-solid foods within a day, including meals and snack. The MFF scoring pattern applied in this study was based on WHO’s recommendations on the number of meals that children belonging to the various age-groups should be fed daily in addition to breastfeeding and as described and applied in previous studies [22, 23]. On the basis of WHO’s recommendations, a score of zero (0) was given to children aged 6–8 months who were fed complementary foods 0–1 times, 1 when fed two times, and a score of 2 when fed more than two times (> 2) over a 24-h period prior to interviewing the mother. For children in the age groups of 9–12 months and 13–23 months, a score of 0 was awarded if a child was fed 0–2 times in a day, a score of 1 was given when a child ate complementary foods three times in a day, and a score of 2 was awarded when a child ate complementary foods more than three times in a day [21]. It is a composite indicator for assessing feeding practices among 6–23 months old children and considers whether the child has been fed a minimum number of times (MFF) and on a diversified diet (MDD) daily [21]. Scoring and coding of the MAD indicator was done by applying the scoring pattern of previous studies [22, 23] A mother’s household decision-making autonomy was based on responses to 15 questions which covered themes on decisions in the respondent’s household about obtaining healthcare, large household purchases, visits to family or relatives, and child healthcare. Each of the questions had four (4) response options – respondent alone, respondent and husband/partner jointly, husband/partner alone and any other household member which were coded as 4, 3, 2 and 1 respectively. The total scores which were between 15 and 60 were re-categorised as low (15–30), medium/average (31- 45) and high (46–60) decision making power similar to the coding of mother’s household decision-making level in related studies [24, 25]. Control and access over finances or financial independence of a mother was assessed based on her responses to 12 questions. Seven (7) of the questions assessed a mother’s ability to have control over money to buy perishable food items, clothes, medicine, toiletries, jewelry, gifts for parents or other family members. Each of the questions had two response options namely- respondent has control (Yes) and no control (No). “Yes” and “No” were coded as 1 and 0 respectively. The other 5 questions assessed the mother’s ability to save a portion of the money she had earned, spend her earnings as she wished and have a say in how the household’s overall income should be spent. Each of these 5 questions were given three response options – no/never, yes/some of the time and yes/ all the time which were coded as 0, 1 and 2 respectively. The total scores ranged between 0 and 17 and were categorised into low (0–8), medium/average (9–12) and high (13–17) financial independence similar to the coding of levels in related studies [24, 26]. The questionnaire was first developed in English and translated to the two local dialects (Ewe and Akan) and back to English to maintain its consistency and readjustments of inconsistent and inaccurate data. Prior to the actual data collection, the questionnaire was pretested on 20 women at Bruben CHPS Zone to ascertain the reliability, language clarity and simplicity of the tools. The questionnaire was checked for completeness daily by the supervisors and the principal investigator. The data collection period was between August and December, that is the minor rainy season, when food is usually in abundance to the beginning of the dry season (December) when food is a little bit scarce. Dietary diversity score (poor, average, good), minimum acceptable diet (adequate, inadequate) and anthropometric indicators (height-for-age z-score [not stunted, stunted], weight-for-age z-score [not underweight, underweight] and weight-for-height z-score [not wasted, wasted]). Maternal- related variables which were categorical in nature included age (< 20, 20–30, 31–40, > 40) marital status (single [never married], cohabiting, married, separated/divorced, widowed) number of living children (parity) (1–3, 4–6, > 6), number of mothers with children under two years of age (1, 2, 3), employment status (not employed in the last 12 months, not currently employed but worked in past 12 months, currently employed),work status/schedule throughout the year (work throughout the year, work seasonally/part of the year, work only once in a while), form of remuneration/payment (cash only, cash and in kind, in kind only), mother’s highest level of education attained (none, primary, JHS/JSS, secondary, tertiary) decision making power (low, medium/average) and financial independence (low, medium/average, high). Socio-demographic characteristics of study participants were described using frequencies and their corresponding percentages. Multinomial logistic regression was used to examine the association between maternal-related factors and the outcome dietary diversity score (DDS) which was a categorical variable with three levels. Binary logistic regression was employed to determine the association between maternal-related factors and minimum acceptable diet (MAD) which was the outcome with two levels. Binary logistic regression was used to determine the influence of maternal factors on anthropometric indicators (height-for-age, weight-for-height and weight-for-age outcomes). The regression models were constructed by firstly determining the independent maternal factors that were significant in the bivariate models at the significance level of 0.05. Subsequently, all the maternal factors that were significant in the bivariate models were used to construct the multivariate models. All statistical tests were two-tailed and p-values < 0.05 were considered to be statistically significant. Stata software (version 15.0) was used for the statistical analysis.