Food Insecurity and Maternal Diet Influence Human Milk Composition between the Infant’s Birth and 6 Months after Birth in Central-Africa

listen audio

Study Justification:
– The study aims to investigate how the mother’s undernourishment status at delivery and maternal dietary factors influence human milk composition during the first 6 months of life in regions with high food insecurity.
– This research is important because the World Health Organization (WHO) and UNICEF recommend exclusive breastfeeding for the first 6 months of life, but there is limited evidence on how food insecurity and maternal diet impact the nutritional content of human milk.
Study Highlights:
– The study followed 48 women and their 50 vaginally born infants in Bangui, Central Africa, from December 2017 to June 2019.
– The researchers assessed the maternal undernourishment status at delivery, maternal diet, and human milk nutrients at 1, 4, 11, 18, and 25 weeks after birth.
– High food insecurity indexes during the follow-up were associated with lower levels of human milk oligosaccharides (HMOs), retinol, fatty acids, and amino acids.
– Women from food-insecure households had higher levels of lactose in their human milk.
– Consumption of meat, poultry, and fish was associated with higher levels of HMOs, total amino acids, and lower levels of lactose in human milk.
Recommendations for Lay Reader and Policy Maker:
– The study highlights the importance of addressing food insecurity to improve the nutritional content of human milk and potentially enhance infant survival and healthy growth.
– Policy makers should prioritize actions to improve food security in regions with high food insecurity to support breastfeeding mothers and promote infant health.
– Lay readers should be aware of the impact of maternal diet and food insecurity on human milk composition and consider the importance of a balanced diet for breastfeeding mothers.
Key Role Players:
– Researchers and scientists in the field of nutrition and maternal health.
– Health policymakers and government officials responsible for addressing food security and promoting breastfeeding.
– Non-governmental organizations (NGOs) working on nutrition and maternal health programs.
– Healthcare providers, including doctors, nurses, and lactation consultants, who can provide guidance and support to breastfeeding mothers.
Cost Items for Planning Recommendations:
– Research funding for conducting studies on the impact of food insecurity on human milk composition.
– Budget allocation for implementing interventions to improve food security in regions with high food insecurity.
– Resources for training healthcare providers on supporting breastfeeding mothers and promoting optimal maternal nutrition.
– Funding for nutrition education programs targeting pregnant women and new mothers to improve their dietary practices.
– Investment in infrastructure and resources to ensure access to nutritious food for vulnerable populations.
Please note that the cost items mentioned above are hypothetical and may vary depending on the specific context and resources available.

The strength of evidence for this abstract is 7 out of 10.
The evidence in the abstract is moderately strong, but there are some areas for improvement. The study design includes a sample size of 46 women and their 48 infants, which is relatively small. Additionally, the study relies on self-reported data from 24-hour recalls and food consumption questionnaires, which may introduce bias. To improve the strength of the evidence, future studies could consider increasing the sample size and using more objective measures of dietary intake, such as biomarkers or dietary records. Additionally, conducting a randomized controlled trial or a longitudinal study with a control group could provide stronger evidence for the relationship between food insecurity, maternal diet, and human milk composition.

Although the World Health Organization (WHO) and UNICEF recommend that infants should be exclusively breastfed for the first 6 months of life, evidence is scarce on how the mother’s undernourishment status at delivery and maternal dietary factors influence human milk (HM) composition during the first 6 months of life in regions with high food insecurity. The maternal undernourishment status at delivery, maternal diet, and HM nutrients were assessed among 46 women and their 48 vaginally born infants in Bangui at 1, 4, 11, 18, and 25 weeks after birth through 24-h recalls and food consumption questionnaires from December 2017 to June 2019 in the context of the “Mother-to-Infant TransmIssion of microbiota in Central-Africa” (MITICA) study. High food insecurity indexes during the follow-up were significantly associated with them having lower levels of many of the human milk oligosaccharides (HMOs) that were measured and with lower levels of retinol (aß-coef = −0.2, p value = 0.04), fatty acids (aß-coef = −7.2, p value = 0.03), and amino acids (aß-coef = −2121.0, p value < 0.001). On the contrary, women from food-insecure households displayed significantly higher levels of lactose in their HM (aß-coef = 3.3, p value = 0.02). In parallel, the consumption of meat, poultry, and fish was associated with higher HM levels of many of the HMOs that were measured, total amino acids (aß-coef = 5484.4, p value < 0.001), and with lower HM levels of lactose (aß-coef = −15.6, p value = 0.01). Food insecurity and maternal diet had a meaningful effect on HM composition with a possible impact being an infant undernourishment risk. Our results plead for consistent actions on food security as an effective manner to influence the nutritional content of HM and thereby, potentially improve infant survival and healthy growth.

Forty-eight women and their 50 vaginally born infants were followed in Bangui from 8 December 2017 to 29 June 2019 in the context of the “Mother-to-Infant TransmIssion of microbiota in Central-Africa” (MITICA) study. Over 200 pregnant women were pre-included either at antenatal care (ANC) visits or in the neighborhoods surrounding the Henri-Izamo maternity facility in Bangui. The recruitment period (December 2017–June 2019) was set in advance due to logistic and financial constraints. All of the women delivering within the laboratory opening hours (8 AM–2 PM) with negative rapid diagnostic test results for HIV, HBV, and HCV at delivery were de facto included in the cohort. Right after delivery, an extended questionnaire on their pregnancy history, the socio-economic status of the household, woman empowerment status, food consumption, and food security status was filled in, in Sango, which is the local language. Additionally, anthropometric measures of the mother and infant were taken at the point of delivery. Furthermore, 8 mL venous blood and 4 mL cord blood were drawn from the mother and the newborn, respectively. The cord blood sample was drawn immediately after cutting the cord from the newborn’s side. After delivery, systematic visits were scheduled at 1, 4, 11, 18, and 25 weeks after birth. At all of the systematic visits, 8 mL HM were collected, in parallel to a 24-h food recall, a food consumption questionnaire, and a questionnaire on the hygienic measures of the household. Due to the close visits at the beginning of the follow-up (birth and one week after birth), the food consumption questionnaires were only addressed once after the delivery (starting at 1 week after delivery). The MITICA study fulfilled the good practices of the Declaration of Helsinki and was approved by the Institutional Review Board (IRB) of the Pasteur Institute (2016-09/IRB) on 28 April 2017, the Ethics Committee of the Faculty of Sciences of Bangui (9/UB/FACSS/CSVPR/17) on 10 April 2017, and the Ministry of Health of the Central-African Republic (189/MSP/DIRCAB/DGPGHU/DGEHU) on 9 June 2017. Informed consent was gathered at the pre-inclusion after a detailed explanation by the clinical research associate, and it was then confirmed at the delivery. More precise details on the MITICA study can be found elsewhere [21]. Maternal diet composition and feeding practices were assessed by analyzing: (i) a 24-h recall questionnaire; (ii) a food consumption questionnaire (including feeding practices); (iii) a food security questionnaire at each follow-up visit. The questionnaires are presented in the supplementary data (Table S1). Briefly, the 24-h recall is an interview that gathers all information about all of the food and portions that were consumed the previous day. The food consumption questionnaire collects information on the different food categories that were eaten by the mother the previous day in a closed, standard questionnaire format following the FAO recommendations [22]. This questionnaire considers meat, poultry, and fish as a joint category. As the literature reports that fatty acid levels are associated with fish consumption, fish was also analyzed separately in these analyses to improve the accuracy of the statistical associations. The Women’s Dietary Diversity Score (WDDS) was obtained for each woman from both the 24-h recall questionnaire and the food consumption questionnaire following the same FAO guidelines [22]. Additional information on hygienic measures was also gathered. The Household Food Insecurity Access Scale (HFIAS) and Household Hunger Scale (HHS) were calculated for measuring the food security of the household [23,24]. The HFIAS is composed of a set of nine questions that appear to distinguish food-insecure from food-secure households across different cultural settings. The HFIAS is used to assess the access component of the prevalence of household food insecurity and to detect changes in food insecurity over time. The HFIAS categories correspond to no food insecurity, mild food insecurity, moderate food insecurity, and severe food insecurity. The HHS has been specifically validated to measure household hunger in food-insecure areas. Moreover, it produces valid and comparable results across different cultures and settings so that the status of different population groups can be described in a meaningful and comparable way. It is divided into little to no hunger in the household, moderate hunger in the household, and severe hunger in the household. The undernourishment status of the women at the point of delivery was determined using their albumin plasma levels (<35 g/L) according to the international standard cut-off values [25,26]. Between 10 AM and noon, and at least two hours after the previous breast feed, 8 mL of foremilk HM were poured manually by the mother into a sterile tube before breastfeeding the infant at the Institut Pasteur de Bangui (IPB). The foremilk HM samples were immediately transferred into a −80 °C freezer, and then sent to the Danone Nutricia Research laboratory facilities in Utrecht, the Netherlands on dry-ice via the Institut Pasteur in Paris, where the HM was pasteurized to avoid any possible infectious contamination. At the Danone Nutricia Research facility, the HM samples were thawed overnight at 4 °C, whereupon they were gently vortexed and aliquoted. Two 250 µL HM aliquots were analyzed for either amino acid (AA) or fatty acid (FA) concentrations by the standard methods that are described in detail elsewhere [27,28,29]. The HM samples were spiked prior to a lipid extraction [30] with C19:0 to enable FA quantification. The FA concentration was analyzed using a gas chromatograph (GC) that was equipped with a flame ionization detector (FID); the processing and derivatization processes were conducted according to Morrison and Smith [27]. For the determination of poly-unsaturated fatty acids (PUFA), a known amount of C19:0 PC was added as an internal standard to 100 µL sample (HM). The lipids were converted to fatty acid methyl esters with methanol + 2% sulphuric acid at 100 °C for 60 minutes. The fatty acid methyl esters (FAMEs) were extracted with hexane and, after an evaporation procedure was performed, they were dissolved in isooctane. One µL of the isooctane was injected into the GC. The FAMEs were separated on a CP-Sil 88 column and detected using a FID detector. The FAME identification was based on their retention time. The relative concentration of them was based on the peak area, and the absolute concentration of them was calculated after their normalization with the C19:0 peak. Free amino acids (FAA) and total amino acids (TAA) were also determined. The TAA included protein-bound ones and FAA. The determination of the TAA required a prior protein hydrolysis, and it covered 15 detectable AA or AA groups. The acidic hydrolysis process converts asparagine into aspartate (when they are combined, this is referred to as Asx) and glutamine into glutamate (when they are combined, this is referred to as Glx). The FAA analysis does not allow the detection of tryptophan (Trp), cysteine (Cys), and proline (Pro), thereby yielding a total of 18 detectable FAAs and taurine. The methods that were used were based on Teerlink et al. [29]. Precisely, the TAAs and FAAs were analyzed as follows: The proteins in the sample were completely broken down to amino acids by an acid hydrolysis procedure with hydrochloric acid. The amount of the separate amino acids in the hydrolysate was determined by a UFLC procedure using a pre-column derivatization with o-phtaldialdehyde and a fluorimetry procedure. For the FAA determination, proteins and polypeptides were precipitated with perchloric acid, and the sample was then centrifuged. The content of the individual amino acids was determined by UFLC using a pre-column derivatization with o-phtaldialdehyde and a fluorimetry procedure for their detection. To analyse the retinol levels, the HM aliquots were treated at ambient temperature with an ethanolic potassium hydroxide solution for 15–20 h. An extract with acetonitrile was prepared, and the concentration of retinol that was in the extract was determined by an high-performance liquid chromatography (HPLC) using UV properties comparing the HM aliquots with standard solutions. The human milk oligosaccharides (HMOs) were analyzed by employing targeted liquid chromatography mass spectrometry (LC-MS)/MS using a validated method as essentially described by Siziba et al., 2021 [31]. The quantitative determination of the HMO concentrations could be performed for the 16 most abundant HMOs and lactose: 2′-fucosyllactose (2′-FL), 3-fucosyllactose (3-FL), 3′-sialyllactose (3′-SL), 4′-galactosyllactose (4′-GL), 6′-galactosyllactose (6′-GL), 3,2′-difucosyllactose (DFL), 6′-sialyllactose (6′-SL), lacto-N-tetraose (LNT), lac-to-N-neotetraose (LNnT), lacto-N-fucopentaose-I (LNFP I), lacto-N-fucopentaose-II (LNFP II), lacto-N-fucopentaose-III (LNFP III), lacto-N-fucopentaose-V (LNFP V), lacto-N-difucohexaose I (LNDFH I), and the sum of the co-eluting lacto-N-difucohexaose II and lacto-N-neodifucohexaose II (LNDFH II + LNnDFH II). The determination of human milk types was based on the presence of specific HMO markers. Precisely, the samples were assigned to HM-type II if LNFP I and LNDFH I were below the lower limit of quantification (LLOQ). HM-type III was assigned to a sample if LNFP II and LNDFH I were below the LLOQ. HM-type IV was assigned to a sample if LNFP I, LNFP II, and LNDFH I were below the LLOQ. Finally, all of the residual HM samples were categorized as belonging to HM-type I. The Simpson’s Diversity index of the HMOs was calculated as the reciprocal sum of the square of the relative abundance of each of the measured HMOs. Blood was drawn using an EDTA tube, and the hemogram was determined as follows: the complete cell blood counts (CBC) and hemoglobin were analyzed using Horiba’s Yumizen 500 and Pentra XLR. The hemoglobin was dosed after the red cells’ lysis. The plasma ferritin analyses were performed using BioMérieux’ multiparametric VIDAS. The plasmatic CRP and albumin analyses were performed using Horiba’s Pentra 400. Iron deficiency was defined when the plasmatic ferritin levels were <70 µg/L in case of inflammation (CRP ≥ 5 mg/L) and when the ferritin levels were <15 µg/L in the absence of inflammation (CRP < 5 mg/L) [32]. For the vitamin assessment, blood was drawn into a lithium-heparin tube and was immediately centrifuged for 15 min at 3000 r/min at 4 °C. For vitamin A and vitamin E, 100 µL of serum were stored in a cryotube at −80 °C at the IPB before being transferred to the service of Biochemistry of the Cochin Hospital in Paris (France) within 2 months. There, the vitamin A and vitamin E levels were determined using HPLC Ultimate 3000 (Thermo Scientific, Waltham, MA, USA) through a HPLC inverse phase and UV detection methods. For the vitamin C assessment, 200 µL of plasma were dissolved into 200 µL of a deproteinization solution of 2 g of meta-phosphoric acid and 15 mL 0.1% EDTA. This was vortexed for 1 min, incubated for 10 min at 4 °C, and then centrifuged for 4 min at 10,000 r/min at 4 °C. Then, the mix was stored at −80 °C until its transfer to the Cochin Hospital, where the vitamin C levels were analyzed using HPLC Ultimate 3000 (Thermo Scientific) through a HPLC inverse phase and UV detection methods at the Biochemistry service. Vitamin A deficiency was defined when the vitamin A levels were <1 µmol/L, and vitamin E deficiency was defined when the vitamin E levels were <11.6 µmol/L. Vitamin C deficiency was defined when the vitamin C levels were <11 µmol/L, according to the WHO definitions [33]. The questionnaires’ data were gathered on the field using REDCap [31,34] electronic data tools that were hosted at Institut Pasteur online platform. The 24-h recall was completed on paper and then translated into a database by a trained nutritionist. Univariate analyses were performed as follows: Spearman’s coefficient was used to evaluate the correlation between the continuous variables (WDDS, HFIAS, number of meals, etc.,) with the nutrient concentration in HM; the Skillings-Mack test was used to analyze the statistical significance of the evolution of the variables over time; a Mann-Whitney test was used to assess the association of the continuous variables with the bivariate variables (food-group consumption and nutrient concentration in HM, nutrient concentration in HM and undernourishment status of the women at the point of delivery, WDDS calculation depending on the evaluation method, e.g., 24-h recall or food-frequency questionnaire, etc.); a Fisher’s exact test was used to analyze the statistical significance of the variables with different categories among the groups (HFIAS groups and consumption of food groups, etc.). Mixed models with a random intercept at the mother’s levels were used to evaluate univariate and multivariate analyses of the maternal diet on the different HM nutrients (retinol, lactose, FA, and AA). Results from the 24-h recall were considered for the final multivariate analyses as they accurately reported the real diet of the women. For the multilevel models, only models with statistically significant results are shown. These statistical analyses were performed using Stata MP Software (Stata Corp, College Station, TX, USA). The statistical significance of the p value was set at p < 0.05.

The study recommends taking consistent actions on food security to improve the nutritional content of human milk (HM) and enhance infant survival and healthy growth. The following innovations are suggested based on the study:

1. Increase access to nutritious foods: Efforts should be made to improve access to nutrient-rich foods such as meat, poultry, fish, and other sources of essential nutrients. This can be achieved through various interventions, including promoting local food production, improving distribution channels, and implementing social safety nets to ensure food availability and affordability.

2. Address undernourishment among pregnant women: Maternal undernourishment at delivery can impact HM composition. Therefore, interventions should focus on improving the nutritional status of pregnant women through adequate antenatal care, supplementation programs, and nutrition education. This can help ensure that infants receive optimal nutrition through breastfeeding.

3. Improve maternal diet: Promoting a diverse and balanced diet for pregnant and lactating women is crucial for enhancing the nutritional quality of HM. Interventions should focus on educating women about the importance of consuming a variety of nutrient-rich foods, including fruits, vegetables, whole grains, and sources of protein. This can be achieved through nutrition counseling, cooking demonstrations, and community-based programs.

4. Enhance food security: Addressing food insecurity is essential for improving HM composition. This can be done through a combination of strategies, including improving agricultural practices, promoting sustainable food production, strengthening social protection programs, and empowering women in decision-making processes related to food security.

By implementing these innovations, it is possible to positively influence the levels of human milk oligosaccharides (HMOs), retinol, fatty acids, and amino acids in HM, which are crucial for infant nutrition and development.
AI Innovations Description
The recommendation based on the study is to take consistent actions on food security as an effective way to improve the nutritional content of human milk (HM) and potentially enhance infant survival and healthy growth. This can be achieved by addressing food insecurity and improving maternal diet. Specifically, interventions should focus on increasing access to nutritious foods, such as meat, poultry, fish, and other sources of essential nutrients. Additionally, efforts should be made to address undernourishment among pregnant women, as their nutritional status at delivery can impact HM composition. By improving food security and maternal diet, it is possible to positively influence the levels of human milk oligosaccharides (HMOs), retinol, fatty acids, and amino acids in HM, which are crucial for infant nutrition and development.
AI Innovations Methodology
The methodology used to simulate the impact of the main recommendations in this abstract on improving access to maternal health involved following a cohort of 48 women and their 50 vaginally born infants in Bangui, Central Africa, from December 2017 to June 2019. The study was conducted as part of the “Mother-to-Infant TransmIssion of microbiota in Central-Africa” (MITICA) study.

The recruitment of participants was done from over 200 pregnant women who were pre-included either at antenatal care visits or in the neighborhoods surrounding the Henri-Izamo maternity facility in Bangui. Women who delivered within the laboratory opening hours and tested negative for HIV, HBV, and HCV were included in the cohort. Questionnaires were administered to gather information on pregnancy history, socio-economic status, food consumption, and food security status in the local language.

Anthropometric measures of the mother and infant were taken at the point of delivery, and blood samples were drawn from the mother and newborn. Systematic visits were scheduled at 1, 4, 11, 18, and 25 weeks after birth, during which human milk samples were collected, and additional questionnaires on food consumption and hygienic measures were administered.

The collected human milk samples were analyzed for various nutrients, including human milk oligosaccharides (HMOs), retinol, fatty acids, and amino acids. Maternal diet composition and feeding practices were assessed through 24-hour recall questionnaires and food consumption questionnaires. The Household Food Insecurity Access Scale (HFIAS) and Household Hunger Scale (HHS) were used to measure the food security of the households.

Statistical analyses, including Spearman’s coefficient, Mann-Whitney test, Fisher’s exact test, and mixed models with a random intercept, were performed to evaluate the associations between maternal diet, food security, and the nutrient composition of human milk.

The results of the study provided insights into the impact of food insecurity and maternal diet on human milk composition and highlighted the importance of addressing food security and improving maternal diet to enhance infant nutrition and development.

This methodology allowed researchers to assess the relationship between food security, maternal diet, and human milk composition, providing valuable information for improving access to maternal health and promoting infant survival and healthy growth in Central Africa.

Share this:
Facebook
Twitter
LinkedIn
WhatsApp
Email