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World Health Organization recommends exclusive breastfeeding for infants for the first 6 months of life, followed by introduction of nutritious complementary foods alongside breastfeeding. Breast milk remains a significant source of nourishment in the second half of infancy and beyond; however, it is not clear whether more breast milk is always better. The present study was designed to determine the association between amount of breast milk intake at 9–10 months of age and infant growth and development by 12–18 months of age. The study was nested in a randomized controlled trial conducted in Malawi. Regression analysis was used to determine associations between breast milk intake and growth and development. Mean (SD) breast milk intake at 9–10 months of age was 752 (244) g/day. Mean (SD) length-for-age z-score at 12 months and change in length-for-age z-score between 12 and 18 months were −1.69 (1.0) and −0.17 (0.6), respectively. At 18 months, mean (SD) expressive vocabulary score was 32 (24) words and median (interquartile range) skills successfully performed for fine, gross, and overall motor skills were 21 (19–22), 18 (16–19), and 38 (26–40), respectively. Breast milk intake (g/day) was not associated with either growth or development. Proportion of total energy intake from breast milk was negatively associated with fine motor (β = −0.18, p =.015) but not other developmental scores in models adjusted for potential confounders. Among Malawian infants, neither breast milk intake nor percent of total energy intake from breast milk at 9–10 months was positively associated with subsequent growth between 12 and 18 months, or development at 18 months.
This was a prospective cohort study, nested in a randomized controlled single blinded trial, the iLiNS‐DOSE trial, conducted in areas surrounding Mangochi District Hospital and Namwera Health Centre in southern Malawi (Maleta et al., 2015). The iLiNS‐DOSE trial was designed to test the efficacy of small quantity lipid‐based nutrient supplements (SQ‐LNS), in doses ranging from 10 to 40 g/day, for supporting infant growth. Healthy infants were eligible for enrolment into the trial if they were 5.50–6.49 months of age, resided in the study area, would be available during the 12‐month study period, and were not concurrently participating in any other clinical trial. Out of 1,932 infants enrolled in the iLiNS‐DOSE trial, 595 mother–infant pairs were invited to participate in a substudy designed to assess the impact of SQ‐LNS supplementation on breast milk intake at 9–10 months. Four hundred infants were randomized into the breast milk intake substudy at enrolment into the main iLiNS‐DOSE trial. Block randomization and a set of opaque envelopes were used to assign participants to both the intervention groups and the present substudy (Maleta et al., 2015). However, because of higher attrition than anticipated, a second phase of recruitment from the main iLiNS‐DOSE trial was implemented to reach the planned sample size. Participants for the second enrolment were selected at random during the remaining period of enrolment for the main iLiNS‐DOSE trial. Specifically, at enrolment, mothers were asked if they would be interested to participate in both the main and the present substudy before they selected the randomization envelop. The main reasons for attrition were that the mother–infant dyads were not always available to provide saliva samples at the assigned time points and/or they were not available for body weight measurements (Kumwenda et al., 2014). Because their saliva and/or body weight data were incomplete, breast milk intake could not be measured reliably, the total number excluded on this basis was 124. We did not observe a significant impact of SQ‐LNS supplementation on breast milk intake among infants at 9–10 months of age (Kumwenda et al., 2014). The same children were prospectively followed until they turned 18 months, their growth was measured at 12 and 18 months, and motor and language development was assessed at 18 months. We then examined the association between amount of breast milk consumed and growth and development among these children. Mother–infant pairs were eligible for the breast milk intake substudy if the infant was enrolled in the main iLiNS‐DOSE trial, infant age was between 9.0 and 10.0 months, the mother was breastfeeding the infant on demand, and the mother and infant would be available for the full study period of 2 weeks. Participants were not eligible if the mother was breastfeeding more than one infant or the mother or infant had a severe illness warranting hospital referral. The trial was registered at ClinicalTrials.gov registration as ID: {“type”:”clinical-trial”,”attrs”:{“text”:”NCT00945698″,”term_id”:”NCT00945698″}}NCT00945698. For each infant, breast milk intakes over a 14‐day period were measured using the dose‐to‐mother deuterium oxide dilution technique developed by Coward, Cole, Sawyer, and Prentice (1982). A comprehensive description of the method is provided elsewhere (Haisma et al., 2003). The details of the assessment of breast milk intake for the present sample have also been described elsewhere (Kumwenda et al., 2014). In brief, on day zero of the substudy, a baseline saliva sample was taken from both the mother and the infant, followed by a 30 g dose of deuterium given to the mother. Additional saliva samples were collected from both the mother and the infant on study Days 1, 2, 3, 4, 13, and 14. Deuterium enrichment in the saliva of both the mother and the infant over the 2‐week study period was measured by Fourier transform infrared spectroscopy (FTIR 8400 Series; Shimadzu Corporation; IAEA, 2010). Using the solver function in Excel, a two compartment steady state model (Coward et al., 1982) was run to estimate mean daily breast milk intake over the 14‐day period. Energy intake from breast milk was calculated by multiplying mean breast milk intake in grams by a factor of 0.67 kcal/g, which is the mean energy content per gram of breast milk (Butte, Lopez‐Alarcon, & Garza, 2002). Daily energy intake from nonbreast milk sources and meal frequency were derived from the dietary intake data assessed by 4‐pass 24‐hr interactive dietary recalls (Ferguson et al., 1995; Hemsworth et al., 2016) on 2 days, approximately 1 week apart, during the same 14‐day period. Details of dietary intake assessment have been provided elsewhere (Hemsworth et al., 2016). Briefly, daily energy from complementary foods consumed by infants was calculated as the average from two recall days. A meal was defined as any feeding episode where the infant consumed a starchy staple in the form of a porridge (phala) or thick porridge (nsima) or boiled rice, and the number of such meals was summed for each day. Meal frequency was defined as the average of this sum across the 2 days. Breastfeeding frequency was assessed using a food frequency questionnaire from the main iLiNS‐DOSE trial (Arimond et al., 2017). Precoded responses (0 = Not at all; 1 = only at night; 2 = very little, only 1, or 2 times during the day; 3 = moderately, about 3 to 5 times during the day; 4 = very often, at least 6 times during the day) were read to mothers, who were asked to identify the response that most closely matched the frequency of breastfeeding the infant in the previous day. Response 4 was categorized as high breastfeeding frequency. Anthropometric measurements were taken at mean (SD) ages 5.9 (0.3) months (baseline), 12.0 (0.5) months, and 18 (0.8) months by trained data collectors, who were routinely supervised and retrained every 3 months; all measurements were done in triplicate. Measuring equipment was calibrated on a regular basis. Mothers were weighed in light clothing to the nearest 0.01 kg using an electronic scale (SECA 846; Chasmors Ltd, London England) and height was measured to the nearest 0.1 cm using a stadiometer (Harpenden; Holtain Ltd, Crosswell, UK). Infants were weighed nude to the nearest 0.01 kg using an electronic scale (SECA 735; Chasmors Ltd, London England) and length was measured to the nearest 1 mm using a length board (Harpenden Infantometer, Holtain Limited, Crosswell, Crymych, UK). Length‐for‐age z‐scores (LAZ) were calculated using the World Health Organization Child Growth Standards (WHO, Multicentre Growth Reference, & Study Group, 2006). Change in LAZ‐score was calculated by subtracting z‐score at 12 months from z‐score at 18 months. Developmental assessment was conducted by trained fieldworkers who were evaluated for reliability and retrained every 6 months. Children were assessed 53 weeks after enrolment, at a mean age of approximately 18 months. Motor development was assessed using the Kilifi Developmental Inventory, which is a tool that was developed in Kenya based on several standard tests originating in high‐income countries, including the Griffiths Mental Development Scale and the Merrill‐Palmer Scales (Abubakar, Holding, van Baar, Newton, & van de Vijver, 2008). Children were evaluated on 35 gross motor skills, such as walking and climbing, and 34 fine motor skills, such as threading beads on a string. The score was the total number of skills the child successfully completed in each of the subscales (gross and fine motor) and the total motor score (sum of all 69 skills). Language development was assessed using an adapted version of the MacArthur‐Bates Communicative Development Inventory (Fenson et al., 2007), based in part on previous adaptations of this tool in Bangladesh (Hamadani et al., 2010) and Kenya (Alcock et al., 2010). The score was the total number of meaningful words the child was able to say out of a 100‐word vocabulary checklist reported through an interview with a caregiver. We measured developmental stimulation from the environment using the Family Care Indicators score (Kariger et al., 2012), which was the sum of the source of play materials (3 items), variety of play materials (7 items), whether or not books or magazines were present in the home (2 items), and activities items (6 items) indicating whether any adult has engaged in each of six activities with the child in the past 3 days (maximum 18 points). Social‐demographic data (maternal education and age, household assets) were collected during enrolment into the main iLiNS‐DOSE trial through interviews using structured questionnaires. The household asset index was constructed using principal components analysis (Vyas & Kumaranayake, 2006) and was standardized with a mean of zero and standard deviation of one. The index reflected baseline ownership of a set of assets (radio, television, refrigerator, cell phone, and stove), drinking water supply, sanitation facilities, and flooring materials. The Household Food Insecurity Access scale is a continuous measure of the degree of food insecurity (not actual food quality or intake) in the household based on experiential questions. The Household Food Insecurity Access scale is based on a set of questions that captures perceptions and reported experiences of three domains of food insecurity: anxiety and uncertainty about the household food supply; insufficient quality; and insufficient food intake and its physical consequences (Coates, Swindale, & Bilinsky, 2007). Each household received a score from 0 to 27 based on a simple sum of the frequency of occurrence of each food insecurity condition. The higher the score, the higher the degree of household food insecurity experienced in the previous 4 weeks. This study is based on a total sample size of 358 infants from the substudy designed to assess the impact of LNS on breast milk intake (Kumwenda et al., 2014). The sample size was determined for the primary outcome of the breast milk intake substudy. The calculation took into account the WHO (1998) average breast milk intake at 9–11 months of age of 616 ± 172 g/day; on this basis, a sample size of 89 mother–infant pairs per group was needed to detect a group difference in milk intake of ~86 g/day between the four supplementation groups (0, 10, 20, or 40 g; a = 0.05, b = 0.80, effect size = 0.5); the number was increased to 100 per group to account for attrition, which was estimated as 12%. However, the final sample sizes used in different models in this analysis are lower than the total sample size because of missing values. With a sample size of ≥158 for each model, our study had over 80% power to detect a correlation coefficient of 0.2 at the significance level of 5%. Data analyses were done using STATA (version 12; STATA Corp, College Station, TX). Continuous variables were assessed for normality to establish the need for data transformation. Fine, gross, and total motor development scores were skewed (skewness > 1) therefore were log (k‐x) transformed, where k refers to the maximum score, then multiplied by minus one (−1). This transformation reduced skewness to <1 and preserved the original direction of the score (higher is better). For all other scores, the skewness was <1 and therefore did not require transformation. Bivariate analysis was conducted using simple linear regression to assess the independent association between breast milk intake or percent of total energy intake from breast milk and each outcome (attained LAZ at 12 months, change in LAZ between 12 and 18 months, motor and language scores). The following covariates were identified a priori to be included in the adjusted models based on their known biologically plausible relationship with growth and development: maternal education and height, infant weight at 9–10 months, household asset score, family care index, and household food insecurity. Presence of multicollinearity and adjusted associations between the two dietary variables and growth and development were assessed using multiple linear regressions. The p value of ≤.05 was considered statistically significant for all tests.
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