Child undernutrition is widespread in low- and middle-income countries (LMIC) and is associated with health and economic losses. Undernutrition is estimated to contribute to 3.1 million deaths per year in children less than 5 years of age. A complex causal and contextual factors contributing to child undernutrition have been assessed, but maternal depression, which could contribute to child undernutrition by interfering with the mother’s child caring practice and ability, has been received little attention. The objective of this study was to assess the association between maternal postpartum depression symptoms and infant (5–10 months of age) stunting in northern Ethiopia. A community-based cross-sectional study was conducted among mother–infant pairs (n = 232) between March and April 2018. Through interviewer-administrated questionnaire, information on sociodemographic variables were collected, and maternal depression symptoms were assessed using the Edinburgh Postnatal Depression Scale (EPDS≥13). Infants’ length and weight were measured and converted to length and weight for age Z scores using the WHO growth standards. Breastfeeding was a norm, but the adequacy of complementary feeding practice was sub-optimal. Only 25% of the infants met the minimum meal frequency (MMF), less than 10% met the minimum dietary diversity (MMD; 9%) or minimum acceptable diet (7%). Maternal depression was prevalent (22.8%) and was significantly associated with inappropriate complementary feeding and stunting (P 30 min), washing clothes, land preparation, weeding, manual mowing, threshing, grinding and pounding grain and terracing. The final components which explained 70.6% of the total variance were retained and women were classified into three categories (low, medium and heavy) of workload based on their scores. Data on infant feeding practices were assessed using the WHO IYCF indicators (WHO, 2008). Early initiation of breastfeeding, exclusive and continued breastfeeding, introduction to complementary foods and complementary feeding indicators such as MMF, MMD and minimum adequate diet were assessed. Foods consumed in the 24 h prior the survey were categorized into the following seven food groups to calculate the dietary diversity score: (i) grains, roots and tubers; (ii) legumes and nuts; (iii) dairy products; (iv) eggs; (v) flesh foods (meat, fish, poultry and organ meats); (vi) vitamin A‐rich fruits and vegetables; and (vii) other fruits and vegetables. The proportion of breastfed infants meeting the MMF (≥3) and the MMD score (≥4) was calculated. The place of delivery of the infant and immunization status was recalled by the mother, and whenever available was confirmed by checking the immunization cards. Infant illness (morbidity) and healthcare‐seeking practices of the mother were assessed through maternal recall of signs and symptoms related to acute respiratory infections, diarrhoea, cough and/or cold and fever over the 2 weeks prior the survey. Maternal depression was assessed using the Edinburgh Postnatal Depression Scale (EPDS) (Cox, Holden, & Sagovsky, 1987) which included 10 items. Mothers rated the extent to which each item matched their feelings during the 7 days prior to the survey. Possible scores ranges from 0 to 30, with higher scores indicating greater severity of depression. A score of 13 and above indicated the postnatal depression. The EPDS has been used as a screening tool for detecting postnatal depression in different cultures (Kakyo et al., 2012) and has been used in several African countries (Madeghe, Kimani, Stoep, Nicodimos, & Kumar, 2016; Ukaegbe, Iteke, Bakare, & Agbata, 2012; Yator, Mathai, der Stoep, Rao, & Kumar, 2016). A validation study in Ethiopia also demonstrated the acceptability and utility of the Amharic version for use as a screening tool for postnatal depression (Tesfaye, Hanlon, Wondimagegn, & Alem, 2009). The internal consistency measured by Cronbach’s alpha (0.80) was acceptable. Data were checked, coded and entered into SPSS, v. 20, for analysis. Categorical data were analysed by descriptive statistics (frequency and percentage), whereas range, mean and standard deviations were used to present continuous variables. The normal distribution of the data was checked with the Kolmogorov‐Smirnov test (Mishra et al., 2019). Bivariate analyses were conducted, and all variables with P < .25 were included in multivariate logistic regression. The model fit was checked using the Hosmer–Lemeshow goodness of fit test. Statistical significance was considered at the 95% confidence interval, and both crude and adjusted odds ratios are reported.
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