Independent and combined effects of improved water, sanitation, and hygiene (Wash) and improved complementary feeding on early neurodevelopment among children born to hiv-negative mothers in rural zimbabwe: Sub study of a cluster-randomized trial

listen audio

Study Justification:
– Globally, a significant number of children are at risk of compromised neurodevelopment due to poverty, stunting, and lack of stimulation.
– This study aimed to investigate the independent and combined effects of improved water, sanitation, and hygiene (WASH) and improved infant and young child feeding (IYCF) on early child development (ECD) among children in rural Zimbabwe.
Highlights:
– The study was a cluster-randomized community-based trial involving 5,280 pregnant women from 211 clusters.
– The primary outcomes measured were child length-for-age Z-score and hemoglobin concentration at 18 months of age.
– A subgroup of 1,655 HIV-unexposed children was recruited for the ECD substudy, which assessed child development at 2 years of age using various assessment tools.
– The study found little evidence that the IYCF and WASH interventions caused clinically important improvements in child development at 2 years of age.
– The study suggests that interventions directly targeting neurodevelopment or addressing the multifactorial nature of neurodevelopment may be needed to support healthy development in vulnerable children.
Recommendations:
– Further research is needed to identify interventions that specifically target neurodevelopment or comprehensively address the multiple factors influencing child development.
– Policy makers should consider implementing interventions that go beyond improved water, sanitation, and hygiene and improved infant and young child feeding to support healthy development in vulnerable children.
Key Role Players:
– Researchers and scientists specializing in child development, public health, and nutrition.
– Government officials and policymakers responsible for implementing interventions related to child development, water, sanitation, and hygiene, and nutrition.
– Community health workers and healthcare providers involved in delivering interventions and assessing child development.
Cost Items for Planning Recommendations:
– Research and data collection costs, including personnel salaries, training, and equipment.
– Intervention implementation costs, such as the construction of latrines, provision of handwashing stations, delivery of hygiene supplies, and distribution of nutrient supplements.
– Monitoring and evaluation costs to assess the effectiveness of interventions and measure child development outcomes.
– Costs associated with community engagement and behavior change communication to promote and sustain interventions.
– Costs for training and capacity building of healthcare providers and community health workers involved in delivering interventions and assessing child development.

The strength of evidence for this abstract is 7 out of 10.
The evidence in the abstract is moderately strong. The study design is a cluster-randomized trial, which is a robust method. The study enrolled a large number of pregnant women (5,280) and evaluated the effects of improved water, sanitation, and hygiene (WASH) and improved infant and young child feeding (IYCF) on early child development (ECD) among children in rural Zimbabwe. The primary outcomes were child length-for-age Zscore and hemoglobin concentration at 18 months of age. The study found little evidence that the interventions caused clinically important improvements in child development at 2 years of age. To improve the strength of the evidence, future studies could consider increasing the sample size, conducting a longer follow-up period, and including a control group that receives no intervention.

Background Globally, nearly 250 million children (43% of all children under 5 years of age) are at risk of compromised neurodevelopment due to poverty, stunting, and lack of stimulation. We tested the independent and combined effects of improved water, sanitation, and hygiene (WASH) and improved infant and young child feeding (IYCF) on early child development (ECD) among children enrolled in the Sanitation Hygiene Infant Nutrition Efficacy (SHINE) trial in rural Zimbabwe. Methods and findings SHINE was a cluster-randomized community-based 2×2 factorial trial. A total of 5,280 pregnant women were enrolled from 211 clusters (defined as the catchment area of 1–4 village health workers [VHWs] employed by the Zimbabwean Ministry of Health and Child Care). Clusters were randomly allocated to standard of care, IYCF (20 g of small-quantity lipidbased nutrient supplement per day from age 6 to 18 months plus complementary feeding counseling), WASH (ventilated improved pit latrine, handwashing stations, chlorine, liquid soap, and play yard), and WASH + IYCF. Primary outcomes were child length-for-age Zscore and hemoglobin concentration at 18 months of age. Children who completed the 18- month visit and turned 2 years (102–112 weeks) between March 1, 2016, and April 30, 2017, were eligible for the ECD substudy. We prespecified that primary inferences would be drawn from findings of children born to HIV-negative mothers; these results are presented in this paper. A total of 1,655 HIV-unexposed children (64% of those eligible) were recruited into the ECD substudy from 206 clusters and evaluated for ECD at 2 years of age using the Malawi Developmental Assessment Tool (MDAT) to assess gross motor, fine motor, language, and social skills; the MacArthur–Bates Communicative Development Inventories (CDI) to assess vocabulary and grammar; the A-not-B test to assess object permanence; and a self-control task. Outcomes were analyzed in the intention-to-treat population. For all ECD outcomes, there was not a statistical interaction between the IYCF and WASH interventions, so we estimated the effects of the interventions by comparing the 2 IYCF groups with the 2 non-IYCF groups and the 2 WASH groups with the 2 non-WASH groups. The mean (95% CI) total MDAT score was modestly higher in the IYCF groups compared to the non-IYCF groups in unadjusted analysis: 1.35 (0.24, 2.46; p = 0.017); this difference did not persist in adjusted analysis: 0.79 (−0.22, 1.68; p = 0.057). There was no evidence of impact of the IYCF intervention on the CDI, A-not-B, or self-control tests. Among children in the WASH groups compared to those in the non-WASH groups, mean scores were not different for the MDAT, A-not-B, or self-control tests; mean CDI score was not different in unadjusted analysis (0.99 [95% CI −1.18, 3.17]) but was higher in children in the WASH groups in adjusted analysis (1.81 [0.01, 3.61]). The main limitation of the study was the specific time window for substudy recruitment, meaning not all children from the main trial were enrolled. Conclusions We found little evidence that the IYCF and WASH interventions implemented in SHINE caused clinically important improvements in child development at 2 years of age. Interventions that directly target neurodevelopment (e.g., early stimulation) or that more comprehensively address the multifactorial nature of neurodevelopment may be required to support healthy development of vulnerable children.

The design and methods of SHINE have been previously described [27]; the full protocol and statistical analysis plan are at https://osf.io/w93hy. Briefly, SHINE was a cluster-randomized community-based 2×2 factorial trial testing the independent and combined effects of a WASH intervention and an IYCF intervention on linear growth and hemoglobin at 18 months of age [27]. The study area comprised 2 rural districts of central Zimbabwe, which were divided into 212 clusters, defined as the catchment area of 1–4 village health workers (VHWs) employed by the Zimbabwean Ministry of Health and Child Care. Clusters were randomly allocated to 1 of 4 treatment arms (standard of care [SOC] alone, WASH, IYCF, or WASH + IYCF) at a public event using highly constrained randomization, which achieved balance across arms on 14 measures of geography, demography, water access, and sanitation coverage [28] (described more fully in S1 Text). Due to the nature of the interventions, masking was not possible. Between November 2012 and March 2015, VHWs identified pregnancies through prospective surveillance; women were eligible if they permanently resided in 1 of the rural study clusters, were confirmed pregnant ( 0.1), and selecting a range of 100 words found to be easy (70%–100% said their child knew the word), moderate (40%–70% said their child knew the word), and hard (only 20%–40% said their child knew the word). This vocabulary checklist was then piloted with another 30 mothers, and inter-rater reliability was tested to ensure 97% agreement between testers on the same list with the same mother [38]. This process was conducted only in Shona-speaking households. We included the CDI grammar checklist for 2-year-olds to increase the number of items specifically targeting language development, which changes dramatically at this age. The A-not-B test assesses object permanence and working memory [39]. This task requires the child to watch as a treat is hidden under 1 of 2 bowls (A or B); after a brief delay, the child is asked to find the treat under one of the bowls and in doing so, to remember (through object permanence) which one of the bowls it was hidden under (A or B). The exercise is repeated 10 times, switching which bowl the treat is hidden under according to a strict protocol for all 10 episodes to check that the child has no perseveration error. Children not completing a full set of 10 tests were excluded from analysis. The self-control task [40] we used assesses impulsivity. The child is required to watch as a treat is promised to them, but they have to wait for 2 minutes to take it. The test is first conducted with a covered treat, then with an uncovered treat. Self-control was defined as a child who waited for 2 minutes. We conducted and scored the test in a similar way to that done in Uganda [41]. We prespecified that the primary inferences would be based on children of mothers testing HIV-negative during pregnancy; these results are presented in this paper. Results among children born to HIV-positive mothers will be reported separately. The prespecified primary outcomes of the ECD substudy were total MDAT score (out of 138), MDAT gross motor score (out of 36), MDAT fine motor score (out of 36), MDAT social score (out of 30), MDAT language score (out of 36), MacArthur–Bates CDI vocabulary checklist (total number of words known out of 100), A-not-B score (out of 10), and the proportion of children with self-control. The prespecified secondary outcome was the proportion of children who used imperatives or the progressive tense, plurals, or combined 2 words as assessed using the MacArthur–Bates CDI grammar checklist. We undertook several validation and quality control procedures. Nurses underwent 6-monthly refresher training and standardization (using non-SHINE children), undertaking an ECD assessment that was observed and double-marked by a gold-standard assessor; percentage agreement had to be >85% to pass the standardization. At each standardization (3 in total), nurses were asked to measure 1 child twice (once in the morning and once in the afternoon), for which intra-class correlations for each test were as follows: MDAT, 0.88 (95% CI 0.82, 0.94); MacArthur–Bates CDI, 0.94 (95% CI 0.90, 0.96); A-not-B test, 0.85 (95% CI 0.80, 0.90); and self-control task, 0.80 (95% CI 0.76, 0.85). Supportive supervision of ECD assessments was undertaken during monthly field visits, with corrective or reinforcing feedback provided to nurses. Finally, 5% of assessments in the field were video-recorded. These assessments were then reviewed and double-marked by a psychologist with expertise in all tests (JC) and a pediatrician with advanced training in child neurodevelopment and Shona language proficiency (GK). Percentage agreement was 93% for MDAT fine motor, 90% for MDAT language, 97% for A-not-B, and 91% for the self-control task. Only the nurse’s score was used in the final analysis. All analyses were intention-to-treat at the child level. For tests with continuous outcomes (MDAT, MacArthur–Bates CDI, and A-not-B test), the absolute difference in mean score between treatment groups was estimated. For tests with dichotomous outcomes (self-control and grammar), the relative risk (RR) of passing the test was estimated in comparing treatment groups. Although the study was not powered to detect a statistical interaction between the IYCF and WASH treatments, it was estimated for each outcome. We accounted for the interaction in the model if it was significant (p 0.25 SD for continuous outcomes; RR > 2 or <0.5 for dichotomous outcomes). Otherwise, we used a regression model with 2 terms to represent the treatment arms; we estimated the effect of IYCF by comparing the 2 IYCF arms with the 2 non-IYCF arms and estimated the effect of WASH by comparing the 2 WASH arms with the 2 non-WASH arms. If interaction was significant, we used a regression model with 3 terms to represent the 4 treatment arms. We used generalized estimating equations that accounted for within-cluster correlation to estimate effect size, unadjusted for other covariates, with an exchangeable working correlation structure [39]. A log-binomial specification was used to facilitate estimation of RRs. We compared baseline characteristics between arms while handling within-cluster correlation using multinomial and ordinal regression models with robust variance estimation, and Somers’ D for medians. We used Stata (version 14.1) for all analyses. Adjusted analyses controlled for prespecified baseline covariates (as in our statistical analysis plan), which were initially assessed in bivariate analyses to identify those with an important association with the outcome (for dichotomous outcomes: p 2.0 or < 0.5; for continuous outcomes: p 0.25 SD). Selected covariates were entered in a multivariable regression model; a forward stepwise selection procedure was implemented, with p < 0.2 required for a variable to enter the model. A per-protocol analysis was conducted to examine intervention effects when delivered at high fidelity (prespecified for WASH + IYCF arm as receiving all 10 core modules; for other arms predefined as receiving all modules scheduled at the same time-points when WASH + IYCF core modules were delivered). A prespecified subgroup analysis by child sex was planned if the interaction terms were p 80% power and a type I error rate of 5%, assuming an ICC of 0.07, 10 children per cluster, 33 clusters per arm, and a total of 132 clusters. We therefore aimed to recruit at least 1,320 children. The Medical Research Council of Zimbabwe and the Institutional Review Board of the Johns Hopkins Bloomberg School of Public Health approved the study protocol (Zimbabwe: MRCZ/A/1675; Johns Hopkins University: IRB#4205). The ECD substudy protocol was included as an amendment to the main SHINE trial protocol, submitted to and approved by the 2 institutional review boards. The SHINE statistical analysis plan included the prespecified ECD outcomes. These documents can be found in S1 Text and at https://osf.io/w93hy. An independent data and safety monitoring board comprising 2 physicians from Zimbabwe and a statistician from the UK (listed in Acknowledgments) reviewed interim adverse event data in the main trial between enrollment and 18 months of age, but not in the ECD substudy since no interventions were provided between 18 and 24 months of age. The trial was registered at ClinicalTrials.gov ({“type”:”clinical-trial”,”attrs”:{“text”:”NCT01824940″,”term_id”:”NCT01824940″}}NCT01824940).

The study mentioned in the description is titled “Independent and combined effects of improved water, sanitation, and hygiene (WASH) and improved complementary feeding on early neurodevelopment among children born to HIV-negative mothers in rural Zimbabwe: Sub study of a cluster-randomized trial.” The study aimed to assess the impact of improved water, sanitation, and hygiene (WASH) and improved infant and young child feeding (IYCF) on early child development (ECD) among children enrolled in the Sanitation Hygiene Infant Nutrition Efficacy (SHINE) trial in rural Zimbabwe.

The study used a cluster-randomized community-based 2×2 factorial trial design. A total of 5,280 pregnant women were enrolled from 211 clusters, and clusters were randomly allocated to standard of care, IYCF, WASH, or WASH + IYCF interventions. The primary outcomes measured were child length-for-age Z score and hemoglobin concentration at 18 months of age. Children who completed the 18-month visit and turned 2 years between March 1, 2016, and April 30, 2017, were eligible for the ECD substudy.

The ECD substudy assessed child development at 24 months of age using various assessment tools, including the Malawi Developmental Assessment Tool (MDAT) to assess gross motor, fine motor, language, and social skills; the MacArthur-Bates Communicative Development Inventories (CDI) to assess vocabulary and grammar; the A-not-B test to assess object permanence; and a self-control task. The study analyzed the effects of the interventions on these outcomes.

The study found little evidence that the IYCF and WASH interventions implemented in SHINE caused clinically important improvements in child development at 2 years of age. The study suggests that interventions directly targeting neurodevelopment or addressing the multifactorial nature of neurodevelopment may be required to support healthy development of vulnerable children.

The study had some limitations, including the specific time window for substudy recruitment, which meant that not all children from the main trial were enrolled. The study also focused on children born to HIV-negative mothers, and results for children born to HIV-positive mothers will be reported separately.

Overall, the study highlights the need for comprehensive interventions that directly target neurodevelopment to improve child development outcomes.
AI Innovations Description
The recommendation to improve access to maternal health based on the study is to implement interventions that directly target neurodevelopment or comprehensively address the multifactorial nature of neurodevelopment. The study found little evidence that the improved water, sanitation, and hygiene (WASH) and improved infant and young child feeding (IYCF) interventions implemented in the SHINE trial caused clinically important improvements in child development at 2 years of age. Therefore, it suggests that interventions focusing on early stimulation or a more comprehensive approach may be needed to support the healthy development of vulnerable children.
AI Innovations Methodology
The study described is a cluster-randomized trial that aimed to test the independent and combined effects of improved water, sanitation, and hygiene (WASH) and improved infant and young child feeding (IYCF) on early child development (ECD) among children in rural Zimbabwe. The study enrolled 5,280 pregnant women from 211 clusters and allocated them to one of four treatment arms: standard of care, IYCF, WASH, or WASH + IYCF. The primary outcomes measured were child length-for-age Z score and hemoglobin concentration at 18 months of age.

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

1. Define the target population: Identify the specific population that would benefit from improved access to maternal health. This could include pregnant women, new mothers, or women of reproductive age.

2. Identify the barriers to access: Determine the main barriers that prevent women from accessing maternal health services. This could include factors such as distance to health facilities, lack of transportation, cost of services, cultural beliefs, or lack of awareness.

3. Develop interventions: Based on the identified barriers, develop interventions that address these challenges and improve access to maternal health. This could include initiatives such as mobile health clinics, community health workers, transportation subsidies, or educational campaigns.

4. Estimate the impact: Use available data and evidence to estimate the potential impact of the interventions on improving access to maternal health. This could involve analyzing data from similar interventions or conducting modeling studies to project the potential outcomes.

5. Conduct a pilot study: Implement the interventions on a small scale to assess their feasibility and effectiveness. This could involve selecting a sample population and implementing the interventions for a specific period of time, while collecting data on access to maternal health services.

6. Evaluate the results: Analyze the data collected during the pilot study to evaluate the impact of the interventions on improving access to maternal health. This could include measuring changes in the number of women accessing services, improvements in health outcomes, or changes in knowledge and behavior related to maternal health.

7. Scale up and monitor: If the pilot study shows positive results, consider scaling up the interventions to reach a larger population. Continuously monitor and evaluate the interventions to ensure their effectiveness and make any necessary adjustments.

By following these steps, it is possible to simulate the impact of recommendations on improving access to maternal health and develop effective strategies to address the challenges faced by pregnant women and new mothers.

Partilhar isto:
Facebook
Twitter
LinkedIn
WhatsApp
Email