Small-quantity lipid-based nutrient supplements, with or without added zinc, do not cause excessive fat deposition in Burkinabe children: results from a cluster-randomized community trial

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Study Justification:
The purpose of this study was to evaluate the potential effects of small-quantity lipid-based nutrient supplements (SQ-LNS) on fat deposition in children in Burkina Faso. The study aimed to address concerns that interventions to address undernutrition may contribute to obesity risk. Specifically, the study tested the hypothesis that SQ-LNS might increase fat deposition in children, and that additional zinc provided through SQ-LNS or dispersible tablets would increase fat-free mass (FFM) accretion.
Highlights:
– The study was conducted in the Dandé Health District in Burkina Faso, where childhood undernutrition is common and malaria is endemic.
– A total of 3220 children aged 9-10 months were enrolled in the study, with 2435 in the intervention cohort (IC) and 785 in the non-intervention cohort (NIC).
– Children in the IC were randomly assigned to receive different amounts of zinc incorporated in SQ-LNS or zinc tablets, while children in the NIC did not receive any supplements.
– Body composition was assessed in a subset of children at 9 and 18 months using the deuterium dilution method.
– The study found that children in the IC had significantly greater change in FFM compared to the NIC, indicating that SQ-LNS increased weight gain and FFM in young children without increasing fat mass (FM) deposition.
– Additional zinc supplementation did not affect changes in FFM or FM.
Recommendations:
Based on the study findings, the following recommendations can be made:
1. Small-quantity lipid-based nutrient supplements (SQ-LNS) can be used as an effective intervention to promote weight gain and fat-free mass (FFM) accretion in young children.
2. Additional zinc supplementation does not appear to have a significant impact on changes in FFM or fat mass (FM) in children.
3. Public health interventions addressing undernutrition should consider incorporating SQ-LNS as a strategy to improve child growth and development.
Key Role Players:
To address the recommendations, the following key role players may be needed:
1. Health policymakers and government officials responsible for nutrition programs and interventions.
2. Public health professionals and researchers with expertise in child nutrition and growth.
3. Non-governmental organizations (NGOs) and international agencies involved in nutrition and child health programs.
4. Health workers and community health workers who can implement and monitor the use of SQ-LNS in community settings.
5. Nutritionists and dietitians who can provide guidance on the appropriate use of SQ-LNS and zinc supplementation.
Cost Items:
While the actual cost of implementing the recommendations will vary depending on the context and specific program design, the following cost items should be considered in planning:
1. Procurement and distribution of small-quantity lipid-based nutrient supplements (SQ-LNS) and zinc tablets.
2. Training and capacity building for health workers and community health workers on the use and administration of SQ-LNS.
3. Monitoring and evaluation activities to assess the impact and effectiveness of the intervention.
4. Communication and awareness campaigns to promote the use of SQ-LNS and raise awareness about its benefits.
5. Research and data collection to further evaluate the long-term effects and cost-effectiveness of SQ-LNS interventions.
Please note that the above cost items are general considerations and may need to be adapted to the specific context and resources available.

The strength of evidence for this abstract is 8 out of 10.
The evidence in the abstract is strong because it is based on a two-stage, cluster-randomized trial design with a large sample size. The study provides detailed information on the methodology, including the randomization process and data collection procedures. The results are presented clearly and include statistical analysis. To improve the evidence, the abstract could include more information on the characteristics of the study population and potential limitations of the study, such as generalizability and potential confounding factors.

Purpose: Public health interventions to address stunting and wasting should be evaluated for possibly contributing to obesity risk. The present study tested the hypothesis that small-quantity lipid-based nutrient supplements (SQ-LNS) might increase fat deposition, and that additional zinc provided via SQ-LNS or in the form of dispersible tablets would increase fat-free mass (FFM) accretion. Methods: Using a two-stage, cluster-randomized trial design, 34 communities were randomly assigned to the intervention cohort (IC) or non-intervention cohort (NIC), and family compounds within the IC were randomly assigned to receive different amounts of zinc (0, 5 or 10 mg zinc) incorporated in SQ-LNS or 5 mg zinc in the form of dispersible tablets along with treatment for diarrhea, malaria and fever. Body composition was assessed in a subset of IC (n = 201) and NIC (n = 74) children at 9 and 18 months using the deuterium dilution method. A mixed linear model was used to examine average change in FFM and % fat mass (%FM) among intervention groups and by cohort. Results: Children in the IC had significantly greater change in FFM (Mean (95% Confidence Interval)) (1.57 (1.49, 1.64) kg) compared to the NIC (1.35 (1.23, 1.46) kg; p = 0.005). There were no significant differences in the change in %FM between the NIC and IC or among the intervention groups. Conclusion: SQ-LNS, along with morbidity treatment increased weight gain and FFM in young children from 9 to 18 months of age without increasing FM deposition. Additional zinc supplementation did not affect changes in FFM or %FM. Trial registration: The study was registered as a clinical trial with the US National Institute of Health (www.ClinicalTrials.gov; NCT00944281).

The iLiNS-ZINC study took place from April 2010 to July 2012 in the Dandé Health District, a rural district in southwestern Burkina Faso, where childhood undernutrition is common and malaria is endemic [21]. The climate alternates between a rainy season from May to September and a dry season from October to April. Agriculture is the main source of income for most households, although food insecurity is highly prevalent [22]. The parent study has been described in detail in previous publications [11, 15, 23, 24]. This trial included two levels of randomization: (1) at the community level and (2) at the concession (extended family compound) level. In the first level-randomization, 34 communities accessible during the rainy season were stratified by health clinic catchment area and were then randomly allocated to intervention cohort (IC, 25 communities) or non-intervention cohort (NIC, 9 communities), in such a way as to ensure balanced cohorts with respect to population size, distance from a paved road, and distance from the main city of Bobo-Dioulasso. In the intervention communities, concessions were randomly allocated to the intervention groups following a pre-generated randomization list prepared by the study statistician. Children in the IC were assigned to one of four treatment groups at the level of the concession to reduce the risk of cross-contamination within the family compound through food sharing. The investigators, field staff, study statistician, and all participants were blinded to the IC groups during the trial and initial phases of data analysis. A total of 3220 children 9–10 months of age were enrolled in the parent study (Fig. 1). Of these, 2435 children were included in the IC and 785 in the NIC. Children were considered eligible if they were permanent residents of the study area and their caregivers planned to be available during the nine-month study period and were willing to accept weekly home visits for morbidity assessments. Children were not enrolled in the study if their hemoglobin concentration (Hb) was < 50 g/L, weight-for-length was < 70th percentile of the National Center for Health Statistics/World Health Organization (NCHS/WHO) growth reference [25], or they had any illness warranting hospital referral or potentially interfering with growth [11, 15, 23]. Flow diagram of participants in the body composition sub-study Children in the IC were assigned to receive one of the following sets of daily supplements from 9 to 18 months of age: (1) SQ-LNS with no added zinc, and placebo tablet (LNS-Zn0); (2) SQ-LNS with 5 mg zinc, and placebo tablet (LNS-Zn5); (3) SQ-LNS with 10 mg zinc, and placebo tablet (LNS-Zn10); or (4) SQ-LNS with no added zinc, and 5 mg zinc tablet (LNS-TabZn5). More information on the nutrient composition of SQ-LNSs is given elsewhere [11]. All the study products were developed for the iLiNS project [16], and provided by Nutriset SAS (Malaunay, France). Supplementation of children in the IC started the day after all baseline data were collected, including the deuterium dilution study of body composition described below. Children in the NIC (N = 785) did not receive SQ-LNS or tablets from 9 to 18 months of age, but received SQ-LNS with 10 mg zinc for a 9-month period after the final saliva samples were collected. Caregivers in the IC communities were instructed to administer 20 g SQ-LNS per day in two separate servings, preferably mixed in a small portion of the child’s meal, and to give the dispersible (zinc or placebo) tablet once daily at least 30 min away from meals to enhance zinc absorption. Adherence to both forms of supplements was assessed by obtaining information from maternal reports on daily administration and consumption of the supplements, and by collecting any remaining SQ-LNS, tablets and empty packages to estimate the disappearance rate each week [24]. At enrollment and throughout the study, the caregivers were advised to continue breastfeeding and to feed diverse local foods to the child. At baseline, all affected children were treated for anemia, fever, malaria, and reported diarrhea following the national health guidelines in Burkina Faso [23]. Hb concentration in capillary blood was measured by Hemocue (Hemocue 201+, HemoCue AB, Ängelholm, Sweden). Children with Hb  0.5 cm or weight measurements differed by > 0.1 kg, a third measurement was completed and the average of the two closest values was used in the analysis. Demographic and socioeconomic data were collected via questionnaire within 15 days of enrollment. Household food insecurity was assessed via the Household Food Insecurity Access Scale (HFIAS) [26]. At 9 and 18 months, dietary intake data and information on breastfeeding practices were obtained using adapted 24-h and 7-day food frequency questionnaires [27]. After enrollment, children in the IC were visited weekly by trained field agents who delivered the supplements and collected data on the children’s general health status, appetite and morbidity symptoms [23]. Treatment was provided in the case of reported diarrhea, reported or confirmed fever, and confirmed malaria based on positive RDT, as described above. Caregivers in the IC were advised to continue the previously assigned preventive supplementation regimens during illness. When any clinical danger sign, episode of diarrhea or malaria with complications, or signs of lower respiratory tract infection were reported, the child was referred to the local health clinic. This paper reports on data obtained from a randomly selected subgroup of children who were included in the “biochemistry subgroup” (Fig. 1), as previously described [15] and who successfully provided saliva samples at both baseline and endline. Only one child from each concession was eligible to be included in the biochemistry subgroup to avoid reduced accuracy of estimation due to intra-cluster correlation. Among the selected children, those who had fever or reported diarrhea on the day of enrollment or on the day of body composition evaluation were not invited to the biochemistry assessment day or excluded on that day. Body composition was assessed using the deuterium dilution technique [28, 29]. We provided a constant dose of 4.0 g deuterium oxide (D2O, 99.8 atom % 2H, Cambridge Isotope Laboratory Inc., Andover, USA) for each assessment to achieve a concentration of > 600 mg D2O/kg saliva, as recommended for analyses using Fourier-transform infrared spectrometry (FTIR). This dose was confirmed to be adequate during pilot studies of ten children, seven male and three female, 13–23 months of age with body weights ranging from 10 to 12 kg and WAZ ranging from − 0.40 SD to 1.32 SD. The pre-weighed doses of the deuterium tracer were prepared in the laboratory of the Institut de Recherche en Sciences de la Santé (IRSS, Bobo Dioulasso), using an analytical balance sensitive to 0.0001 g (Explorer Pro EP114C, Ohaus Corp., Switzerland) that was used only for this purpose. The tracer doses were placed in narrow-mouth bottles (capacity 8 mL, Thermo Scientific Nalgene, NY), sealed with parafilm to reduce the risk of evaporation, and stored in a refrigerator (4 °C) until used within the same week of their preparation. On the day of administration to the child, deuterium doses were transported to the field site in a cooler. On the test day, the protocol was explained to the child’s caregiver. The child was then weighed in duplicate using an electronic scale with 5 g or 10 g graduation, depending on the actual weight of the infant (Model 334, Seca, Hamburg, Germany). Once the child’s weight was recorded, the first saliva sample was collected using small cotton ball(s). The saliva saturated cotton ball(s) were then inserted into a 10 mL-disposable syringe (Elite Medical (Nanjing) Co. LTD, China) and the saliva was expressed into a cryotube (3.6 mL, Nunc™ A/S, Denmark) and placed into a zip-lock bag and stored in a cooler (4–8 °C) for transport the same day to the IRSS laboratory, where they were stored at − 20 °C until the time of analysis. The D2O dose was mixed with a sweet strawberry-flavored syrup before oral administration, and small volumes of the diluted syrup were used to rinse the bottle twice to ensure administration of the full tracer dose. Children were allowed to breastfeed at will during the equilibration period; the amount of breastmilk consumed at each feeding episode was measured using test weighing. All children were also provided with a standardized snack (infant porridge). All foods and beverages consumed by the child were weighed before and after consumption using a portable kitchen balance. At both 2.5 and 3 h after administration of the D20 dose, two post-dose saliva samples were collected and processed as described above for the baseline samples. Both samples collected at 2.5 and 3 h were analyzed in duplicate and the mean was used in data analyses as described in the next section. Studies were discontinued if the deuterium dose was not fully administered to the child (e.g., the child vomited or drooled some of the dose) or the amount of saliva obtained at any time point was insufficient (< 2 mL). Of the 702 infants invited to participate in the body composition assessments, 294 asymptomatic children provided adequate pre- and post-dose saliva samples at both 9 and 18 months of age (Fig. 1). Results are presented herein only for children who provided sufficient saliva samples at both 9 and 18 months of age for analysis of TBW. Data from 19 children were excluded from the final analyses because of implausibly low values (< 2%) for % fat mass (%FM), resulting in a final analytic sample of 275 children (Fig. 1). Isotopic enrichment of saliva specimens was measured by FTIR (Shimadzu FTIR, Model 8400S, Shimadzu, Tokyo, Japan) using validated protocols recommended by the International Atomic Energy Agency (IAEA) [28, 29]. All samples were analyzed in duplicate [except in three cases where the volume was insufficient]. The coefficients of variation (CV) for the duplicate samples obtained at a single time point did not exceed 1%. If the CV of the mean of the four specimens analyzed for the two post-dose time points exceeded 5%, the most extreme value was eliminated, and the final post-dose value was calculated based on the mean of the remaining three values. Deuterium concentrations of the pre-dose and the four post-dose samples (2.5 and 3 h) were determined using a calibration curve, and D2O enrichment was calculated by subtracting the pre-dose value from the final post-dose value. TBW in kg was calculated from the dilution of the deuterium tracer using the equation: TBW (kg) = dilution volume (VolD)/1.041; where VolD = dose of D2O (g) administered to the child divided by the enrichment of D2O in the post-dose sample (mg/kg) [28]. Deuterium oxide overestimates TBW by 1.041 times, and therefore, to correct for the non-exchange of deuterium in the body, the TBW measurement was divided by 1.041. Water intake (from breastmilk or other foods/fluids) during the equilibration period was subtracted from the calculated TBW. FFM was calculated from TBW using a sex- and weight-specific hydration factor [30]. FM was then derived by subtracting the FFM from the total body weight and expressed either in kg or as a percent of body weight (%FM). Acute phase proteins [C-reactive protein (CRP) and α-1-acid glycoprotein (AGP)], were analyzed by ELISA (DBS-Tech in Willstaett, Germany) in plasma samples which were collected from children on the same day as the body composition assessment, as described in details elsewhere [15, 31]. The sample size estimate for the body composition assessment was based on the number of children needed to detect differences in FFM with an effect size of 0.6 SDs for group-wise comparisons among the five groups, with a significance of p ≤ 0.05 and power ≥ 0.80. This anticipated effect size was based on the magnitude of effect found by Arsenault et al. [19]. The estimated sample size for the NIC was inflated for an assumed design effect of 1.5 due to the cluster sampling design, resulting in an estimated total sample requirement of 374 children in the 5 groups (68 in each of the 4 intervention groups and 102 in the NIC). This target sample size was increased to a total of 468 children in the 5 groups to allow for 20% attrition from 9 to 18 months. All outcomes were specified in the statistical analysis plan developed for the International Lipid-based Nutrient Supplements-ZINC (iLiNS-ZINC) Project (https://ilins.ucdavis.edu/). All statistical analyses were carried out using SAS software for Windows (9.3, SAS Institute, Cary, North Carolina). Descriptive statistics (means and standard deviation (SD), least squares mean (LSM) and standard error (SE) and proportions) were used to assess baseline information by study group and cohort, and to compare children who participated in the body composition assessment with those who were not included in these sub-studies. Variables were assessed for normality using the Shapiro–Wilk test. Length-for-age (LAZ), weight-for-age (WAZ) and weight-for-length z-scores (WLZ) were calculated in relation to the WHO Child Growth Standards using SAS macros [32]. In addition to presenting the absolute data for FFM and FM, two indices of height-normalized body composition were calculated: the fat-free mass index (FFMI), calculated as FFM (kg)/length (m)2; and the fat mass index (FMI), calculated as FM (kg)/length (m)2 [33] for all children at 9 months and for 264 children for whom length data were available at 18 months of age. The indices were also plotted on Hattori charts, which are described in detail elsewhere [34]. In the Hattori chart, the x-axis represents FFMI and the y-axis FMI, with additional diagonal lines indicating body mass index (BMI; kg/m2) and %FM. Maternal BMI was calculated as maternal body weight in kg divided by the square of height in m, and classified according to the WHO standards as underweight ( 5 mg/L) and/or AGP (> 1 g/L) were used as markers of inflammation [39]. Participants were categorized into four inflammation classes based on elevation of one or both acute phase proteins, or no inflammation [39]. Definitions of infectious diseases identified in IC children are reported in more detail elsewhere [11, 23]. Briefly, diarrhea was defined as caregiver report of three or more liquid or semi-liquid stools during a 24-h period. Fever was defined as any fever reported by the caregiver or elevated auricular temperature (> 37.5 °C), as measured by the field workers. Malaria was defined as the presence of reported or confirmed fever during the 24 h preceding the morbidity visit, associated with a positive RDT. All models presented in this report use the body composition indicators after adjustment for breastmilk and food/fluids intake during the equilibration period, as recommended [28]. Body composition indicators and changes between baseline and at 18 months were compared by intervention group (four groups) and cohort using mixed models analysis of covariance (PROC MIXED). The models included a random effect of the community to account for intra-community correlation. Intervention group and cohort were used as the main effects. All the outcomes were adjusted for baseline values. Additionally, child sex and age at enrollment, maternal BMI (continuous), baseline child LAZ and WAZ (continuous), study season (rainy or dry), baseline child feeding practices including dietary diversity and consumption of animal source foods (all categorical), maternal education level and marital status were pre-specified and included as covariates. Intervention group means were compared post-hoc using least-square means with the Tukey–Kramer test. Maternal BMI (continuous), baseline child LAZ (continuous variable and categorical variable as defined by the median), child sex, study season (rainy or dry), maternal education level and marital status were identified in advance of the analyses as possible effect modifiers of treatment group and cohort effects on the change in %FM and change in FFM between 9 and 18 months and interactions were examined using PROC MIXED. Ethical approval of the study protocol was provided by the Institutional Review Boards of the Centre Muraz in Bobo-Dioulasso (Burkina Faso) and the University of California, Davis (USA). Caregivers provided separate written, informed consents for their child’s participation in the parent study and for the collection of biological samples, including saliva, for the biochemical and body composition sub-studies.

The iLiNS-ZINC study conducted a cluster-randomized community trial in Burkina Faso to evaluate the effects of small-quantity lipid-based nutrient supplements (SQ-LNS) on children’s body composition. The study aimed to determine if SQ-LNS increased fat deposition and if additional zinc supplementation affected fat-free mass (FFM) accretion. The study found that children in the intervention cohort (IC) who received SQ-LNS had significantly greater change in FFM compared to the non-intervention cohort (NIC). However, there were no significant differences in the change in fat mass (FM) between the IC and NIC or among the intervention groups. Additional zinc supplementation did not affect changes in FFM or FM. The study concluded that SQ-LNS, along with morbidity treatment, increased weight gain and FFM in young children without increasing FM deposition.
AI Innovations Description
The study mentioned is titled “Small-quantity lipid-based nutrient supplements, with or without added zinc, do not cause excessive fat deposition in Burkinabe children: results from a cluster-randomized community trial.” The purpose of the study was to evaluate the effects of small-quantity lipid-based nutrient supplements (SQ-LNS) on fat deposition in children and the impact of additional zinc supplementation on fat-free mass (FFM) accretion. The study took place in the Dandé Health District in Burkina Faso, where childhood undernutrition is common and malaria is endemic.

The study used a two-stage, cluster-randomized trial design, with 34 communities randomly assigned to the intervention cohort (IC) or non-intervention cohort (NIC). Within the IC, family compounds were randomly assigned to receive different amounts of zinc incorporated in SQ-LNS or zinc in the form of dispersible tablets. Body composition was assessed in a subset of children at 9 and 18 months using the deuterium dilution method.

The results showed that children in the IC had significantly greater change in FFM compared to the NIC. However, there were no significant differences in the change in fat mass (FM) between the NIC and IC or among the intervention groups. Additional zinc supplementation did not affect changes in FFM or FM.

The study concluded that SQ-LNS, along with morbidity treatment, increased weight gain and FFM in young children without increasing FM deposition. The additional zinc supplementation did not have an impact on FFM or FM changes.

Overall, the study suggests that small-quantity lipid-based nutrient supplements can be used as an intervention to improve access to maternal health by promoting healthy weight gain and FFM accretion in children.
AI Innovations Methodology
Based on the provided information, here are some potential recommendations for improving access to maternal health:

1. Mobile health clinics: Implementing mobile health clinics that travel to rural areas can help provide access to maternal health services for women who live in remote locations. These clinics can offer prenatal care, postnatal care, and other essential maternal health services.

2. Telemedicine: Utilizing telemedicine technology can help connect pregnant women in remote areas with healthcare professionals. Through video consultations, women can receive prenatal check-ups, guidance on nutrition and exercise, and access to medical advice without having to travel long distances.

3. Community health workers: Training and deploying community health workers can help improve access to maternal health services. These workers can provide education, support, and basic healthcare services to pregnant women in their communities, ensuring that they receive the care they need.

4. Maternal health vouchers: Implementing a voucher system can help women access maternal health services by covering the cost of care. Vouchers can be distributed to pregnant women, allowing them to receive prenatal care, delivery services, and postnatal care at designated healthcare facilities.

To simulate the impact of these recommendations on improving access to maternal health, a methodology could include the following steps:

1. Define the target population: Determine the specific population that will be affected by the recommendations, such as pregnant women in rural areas.

2. Collect baseline data: Gather data on the current access to maternal health services in the target population, including the number of women receiving prenatal care, the distance they have to travel to access care, and any barriers they face.

3. Implement the recommendations: Introduce the recommended interventions, such as mobile health clinics, telemedicine services, community health workers, or maternal health vouchers.

4. Monitor and evaluate: Track the implementation of the recommendations and collect data on the impact they have on access to maternal health services. This can include measuring the number of women utilizing the services, changes in travel distance, and any improvements in health outcomes.

5. Analyze the data: Use statistical analysis to assess the impact of the recommendations on access to maternal health services. Compare the baseline data with the data collected after implementing the interventions to determine if there have been significant improvements.

6. Adjust and refine: Based on the findings, make any necessary adjustments or refinements to the interventions to further improve access to maternal health services.

By following this methodology, it is possible to simulate the impact of the recommendations on improving access to maternal health and make evidence-based decisions on how to best allocate resources and implement interventions.

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