Effectiveness of Integrated Maternal Nutrition Intervention Package on Birth Weight in Rwanda

Inadequate maternal nutrition before and during pregnancy is a principal risk factor for poor fetal development, resulting in low birth weight (LBW) and subsequently, poor child growth. Most studies focus on the impact of nutritional interventions after birth while only a few interventions consider integrated nutrition service packages. Therefore, there is limited evidence on whether integrated maternal nutrition interventions have a positive effect on birthweight. Thus, a post-program quasi-experimental study was carried out to determine the effectiveness of the integrated maternal nutrition intervention package on low birth weight in Rwanda. A total of 551 mother–baby pairs from the intervention and 545 controls were included in the analysis. Data regarding socio-demographic, maternal anthropometric parameters, and dietary diversity were collected using a structured questionnaire. Birth weight was assessed right after delivery, within 24 h. Logistic regression, linear regression, and path analysis were fitted to determine the effectiveness of the intervention on birth weight. The study found that the intervention reduced LBW by 66.99% (p < 0.001) and increased average birth weight by 219 g (p < 0.001). Logistic regression identified reduced risk of LBW among the intervention group (AOR = 0.23; 95%CI = 0.12–0.43; p < 0.001). It was also observed that the direct effect of the intervention on birth weight was 0.17 (β = 0.17; p < 0.001) and the main indirect mediator was maternal MUAC (β = 0.05; p < 0.001). Moreover, maternal passive smoking exposure and MUAC < 23 cm were found as risk factors for LBW. This study has demonstrated that an integrated maternal nutritional intervention package can significantly reduce LBW in low-income settings and should, therefore, be considered to improve birth weight.

The study adopted a quasi-experimental design and was conducted from November 2020 to June 2021. It was a post-intervention evaluation. The intervention group was drawn from two districts namely Kayonza District (rural area) and Kicukiro District (urban area), where the integrated nutrition intervention package (nutrition-specific and nutrition-sensitive) was implemented. The selection criteria for the two districts were based on the high proportion of food insecurity according to the Comprehensive Food Survey and Vulnerability Analysis (26) and locality (rural vs. urban). Similarly, in selecting the control districts three criteria were applied: high food insecurity, no existing nutrition-sensitive and nutrition-specific intervention package, and settlement pattern (rural vs. urban). After considering all the criteria, Gisagara District (rural area) and Gasabo District (urban area) were selected as the comparison control group. In a district, one public district hospital and all health centers were included in the study. The component of the intervention package, which is nutrition-specific, was nutrition education and counseling. The women received nutrition education and counseling by Community Health Workers (CHWs) and nutritionists. First, the nutritionists and CHWs in charge received training on the counseling guide module. Then, the CHWs in charge in turn trained the CHWs at the village level. The trained nutritionist counseled the pregnant women about nutrition during regular antenatal care visits and sessions lasted about 30 to 45 min each. Moreover, the nutritionists also trained the women through cooking demonstrations about a balanced diet through Village Nutrition School. In addition to these, the CHWs gave further nutrition education and counseling at the household level. The CHWs also received in-service training on a monthly basis. The main contents of the educational and counseling guide are indicated in Supplementary Material. The control group, on the other hand, only received routine nutritional education and counseling as per the Rwanda national ante-natal care guidelines adopted from WHO (27). In this intervention, three components were implemented, including promotion of increased agricultural productivity, promotion of financial literacy/economic strengthening, and improved access to WASH services. (1) Increased agricultural productivity: Beneficiaries were taught to practice nutrition-sensitive agriculture and to increase agriculture production using of Bio-Intensive Agriculture Techniques (BIATs). They were grouped into Farmer Field Learning School (FFLS) and advised on how to improve production mainly to attain food security at the household level. (2) Promotion of financial literacy/economic strengthening: The economic status of the women was improved by grouping them into Saving and Internal Lending Communities (SILC) as a way of responding to financial problems that prevent them from attaining better nutritional outcomes. The main methods of SILC were as follows: training those in charge of economic strengthening and project coordinators and district cooperative staff; then the trained staff train the sector cooperative officers, where, they in turn train field agents from the community. Then the field agents sensitize the people about SILC and form the groups. The goal was to help these women better manage their existing resources by teaching them basic financial management skills. This enabled the poor to build up useful lump sums without incurring excessive debt or interest charges. (3) Water, Sanitation, and Hygiene (WASH) interventions: Improved WASH services were implemented using Community Based Environmental Health Promotion Program (CBEHPP) approach through Community Health Clubs (CHC) at the village level. CBEHPP is a hygiene behavior change approach to reach communities and empower them to identify their personal and domestic hygiene needs. CHC and a demonstration site in every village were formed and initiated. The CHCs were responsible for ensuring that the levels of hygiene were monitored, together with the CHW facilitator, who visited each household to observe the household sanitation and environmental conditions. A detailed description of these interventions is presented in Supplementary Material. However, the control group did not receive any of these nutrition-sensitive interventions. The target population was mother–newborn pairs. All pregnant women who came for delivery to all public health facilities in the selected districts were recruited consecutively using the following inclusion criteria: (1) being a permanent resident in the study area and aged between 15 and 49 years, (2) having been enrolled in the selected nutrition intervention package at least 1 year before pregnancy and continued until delivery for intervention group but not for the control group, (3) belonging to wealth category (1 and 2, 4) those without any known medical, surgical, or obstetric problems/conditions, and (5) with live singleton babies and normal spontaneous delivery. The sample size was justified based on a 3.5% effect size and LBW proportion difference between the intervention and control group. This was estimated to detect a reduction of low birth weight from an expected 7% (9) in the control group (general population) to 3.5% in the intervention group. A power of 80%, a confidence level of 95%, and a design effect of 1.25 were considered to achieve the desired sample size. Thus, a total sample size of 1,144 (572 mother–newborn pairs for each study group) was estimated. However, 21 from the intervention and 27 from the control group were excluded from the analysis due to incomplete data. The recruitment flow chart is shown in Figure 1. Recruitment flow chart. Trained midwives/nurses collected the data using a structured quantitative questionnaire. It was composed of basic demographic, lifestyle and obstetric factors, anthropometric and biological measurements, and maternal dietary diversity. To make data collection practices consistent, a standardized operating procedure was developed for all measures. The mothers were interviewed face-to-face in the immediate postpartum period (within 24 h of delivery) using a questionnaire that was translated into the local language (Kinyarwanda). The data collectors were trained on the objectives of the study, participants’ recruitment, and anthropometric measurements. Anthropometric measurements were taken for both the mothers and their newborns. The nutritional status of the mothers was assessed using mid-upper arm circumference (MUAC), body mass index (BMI), and weight gain. MUAC has been identified to have a strong relationship with LBW and it is not affected by any changes like edema common during pregnancy (28). It was measured using flexible non-elastic tape upon recruitment. On the basis of several studies in Africa and due to the need for international comparison, maternal undernutrition was defined as MUAC < 23 cm (28). In addition, antenatal care records were reviewed to retrieve MUAC, weight, and height which are measured during the ANC visits according to Rwandan Ministry of Health guidelines. Weight and height were used to assess body mass index (BMI) and weight gain. Hemoglobin was measured upon recruitment before delivery using a portable HEMOCUE B-Hb photometer according to Rwandan Ministry of Health guidelines. For the newborn babies, weight was measured within 24 h of delivery. The primary outcome of the study was birth weight. It was measured to the nearest 100 g on digital scales at the health facilities. The scales were regularly calibrated as per the manufacturer’s recommendation. Low birth weight was defined as birth weight less than 2,500 g. A food frequency questionnaire was also used to obtain dietary information. This tool included 9 food groups validated by the Food and Agriculture Organization (29). These food groups were cereals and tubers; pulses and legumes; vegetables; fruits; meat, fish and eggs; milk and milk products; oils and fats, and sweets and spices/beverages. Pregnant women presenting to the health facilities for delivery were asked about their frequency of food consumption based on these groups. They were asked to recall what they had eaten in the 24 h preceding the onset of labor. A dietary diversity score was then calculated according to the frequency of food groups consumed by women within the 24 h. A score “1” was assigned to each consumed food group and a score “0” was assigned if not consumed. The scores were aggregated to calculate the total maternal dietary diversity score (DDS) and those who scored below 5 were grouped as inadequate DDS whereas those who scored 5 and above were categorized as having adequate DDS. The analysis was performed using Statistical Package for the Social Sciences (SPSS) version 25.0 IBM New York. Means and percentages were used to summarize continuous and categorical data, respectively. Comparison of the explanatory variables between the intervention and control groups were conducted using an independent sample t-test (to compare means) or Chi-square test (to compare proportions). All statistical significance was set at a p-value less than 0.05. The dependent variable was categorized into LBW (<2,500 g) and normal birth weight (≥2,500 g). To assess the effectiveness of the intervention, logistic regression was conducted by considering all variables with p < 0.2 in the bivariate analysis. The strength of association between LBW and the intervention was presented using an adjusted odds ratio with a corresponding 95% confidence interval. The model fitness was checked using the Hosmer and Lemeshow Test (p-value = 0.214), which indicated the model was an adequate fit. Model classification accuracy was also assured. Linear regression was also carried out for some covariates associated with birth weight as continuous variables. These included maternal hemoglobin concentration (g/dl), maternal MUAC (cm) in the first or second trimester and delivery, BMI in the first trimester, and maternal DDS per 24 h. Multicollinearity, linearity, and interaction were checked among the variables considered in the model. The Scatter plot revealed linearity, and Durbin-Watson (<4) showed independence of the observations/data. The tolerance was greater than 0.1 and the variance of inflation was less than 10, indicating no multicollinearity. Furthermore, fetal growth in the uterus strongly depends on maternal nutritional status and dietary practices, which could also be affected by the intervention. Considering this, a pathway and mediation analysis was conducted to assess the direct and indirect effects of the integrated nutrition intervention package on birth weight. In this case, the outcome variable is birth weight and the predictor for birth weight is the intervention. The nutritional status (MUAC) and dietary diversity score are mediators of the intervention impact. The pathway mediation was analyzed using PROCESS macro version 4.0 for SPSS designed by Hayes (30).

• habtu, michael
• agena, alemayehu gebremariam
• umugwaneza, maryse
• mochama, monica
• munyanshongore, cyprien