Comparison of methods to assess adherence to small-quantity lipid-based nutrient supplements (SQ-LNS) and dispersible tablets among young Burkinabé children participating in a community-based intervention trial

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Study Justification:
– Adherence to supplementation provided during an intervention trial can affect interpretation of study outcomes.
– Better methods are needed to assess adherence in community-based supplementation trials.
Study Highlights:
– The study compared different approaches for estimating adherence to small-quantity lipid-based nutrient supplements (SQ-LNS) and dispersible tablets in a randomized clinical trial in Burkina Faso.
– Adherence to SQ-LNS and tablets was assessed through weekly caregiver interviews and calculation of disappearance rate based on returned packages.
– Additional adherence data were collected through 12-hour home observations and measurement of plasma zinc concentration.
– Apparent adherence to SQ-LNS and dispersible tablets differed depending on the assessment method used.
– Caregiver-reported adherence and disappearance rates showed high average adherence, but home observations and plasma zinc concentration suggested lower adherence.
Study Recommendations:
– Develop better methods to assess adherence in community-based supplementation trials.
– Consider using multiple assessment methods to obtain a more accurate picture of adherence.
– Conduct further research to understand the factors influencing adherence to supplementation.
Key Role Players:
– Researchers and scientists involved in nutrition and public health.
– Community health workers and caregivers.
– Policy makers and government officials responsible for implementing nutrition interventions.
Cost Items for Planning Recommendations:
– Research and development of new adherence assessment methods.
– Training and capacity building for community health workers.
– Data collection and analysis.
– Monitoring and evaluation of adherence interventions.
– Communication and awareness campaigns to promote adherence.
– Supply and distribution of supplementation products.
– Quality control and supervision of adherence assessments.

The strength of evidence for this abstract is 7 out of 10.
The evidence in the abstract is strong, but there are some areas for improvement. The study design is well-described, and the methods used to assess adherence are clearly outlined. The sample size and data collection procedures are also provided. However, the abstract does not provide any results or conclusions from the study. To improve the evidence, the abstract should include a summary of the findings and their implications for future research or practice.

Adherence to supplementation provided during an intervention trial can affect interpretation of study outcomes. We compared different approaches for estimating adherence to small-quantity lipid-based nutrient supplements (SQ-LNS) and dispersible tablets in a randomised clinical trial in Burkina Faso. A total of 2435 children (9-18 months) were randomly assigned to receive daily 20g SQ-LNS with varying contents of zinc and a dispersible tablet containing 0 or 5mg zinc. Adherence to SQ-LNS and tablets was assessed for all children through weekly caregiver interviews, and disappearance rate was calculated based on empty and unused packages returned during home visits. Additional adherence data were collected in different randomly selected subgroups of children: 12-h home observations were completed for children 11 and 16 months of age (n=192) to assess consumption of SQ-LNS and dispersible tablets, and plasma zinc concentration was measured at baseline and 18 months (n=310). Apparent adherence to SQ-LNS and dispersible tablets differed according to the assessment method used. Average daily caregiver-reported adherence to both SQ-LNS and dispersible tablets was 97±6%. Disappearance rates showed similarly high average weekly adherence (98±4%). In contrast, only 63% and 54% of children at 11 and 16 months, respectively, received SQ-LNS during the 12-h home observation periods, and fewer (32% and 27%) received a tablet. The lack of change in plasma zinc concentration after 9 months of supplementation suggests low adherence to the zinc tablet. Better methods are needed to assess adherence in community-based supplementation trials.

The iLiNS‐ZINC study was a community‐based, partially double‐masked, placebo‐controlled, randomised clinical trial conducted in the Dandé health district in southwestern Burkina Faso. Ethical approval was provided by the Institutional Review Boards of the Centre Muraz in Bobo‐Dioulasso (Burkina Faso) and the University of California, Davis (USA). The study was registered with the U.S. National Institutes of Health (http://www.ClinicalTrials.gov; {“type”:”clinical-trial”,”attrs”:{“text”:”NCT00944281″,”term_id”:”NCT00944281″}}NCT00944281). Nine‐month‐old children were identified during periodic censuses conducted in 34 participating communities; 25 communities were stratified to intervention cohort (IC) and 9 to non‐IC (NIC). Further details of the study design are reported elsewhere (Hess et al. 2013). For the present analyses, only children in the IC are considered. Eligible children in these communities were randomly assigned to receive one of the following interventions from 9 to 18 months of age: (1) SQ‐LNS without zinc and a placebo tablet (LNS‐Zn0); (2) SQ‐LNS with 5 mg zinc and a placebo tablet (LNS‐Zn5); (3) SQ‐LNS with 10 mg zinc and a placebo tablet (LNS‐Zn10); or (4) SQ‐LNS without zinc and a 5 mg zinc tablet (LNS‐TabZn5). A second randomisation was completed at the concession level to select subgroups for the different adherence assessment methods [12‐h home observations at 11 and 16 months; knowledge, attitudes and practices (KAP) interview at 15 months; and baseline and final plasma zinc concentration (PZC)]. The first child from each concession was eligible to participate in just one of the adherence sub‐studies (Fig. 1). Scheme of timing of different adherence assessment methods. Caregivers were instructed to give a total of 20 g of SQ‐LNS/day in two separate doses. At the beginning of the study, SQ‐LNS was distributed in 140 g cups for weekly use; this was later changed to 20 g sachets for daily administration. For the cups, caregivers were given a teaspoon and instructed to give one spoonful of SQ‐LNS at each of two separate times during the day, mixed in a small portion of the child’s meal (such as porridge) to ensure that the child consumed the full dose of SQ‐LNS. Similarly, for the sachets, caregivers were instructed to squeeze half of the sachet into a small portion of the child’s meal. For the placebo/zinc dispersible tablets, caregivers were instructed to disperse the tablet in one teaspoon of drinking water or breast milk, and to give the child the entire dose once a day, at least 30 min after a meal. The purpose of the latter instruction was to reduce potential inhibition of zinc absorption if the tablet was given with food (Brown et al. 2007). Both SQ‐LNS and tablets were colour coded by study group and provided by Nutriset SAS (Malaunay, France). In addition to the dietary supplementation instructions, brief feeding messages were provided to promote continued breastfeeding and diverse, nutritious child diets. Instructions on how to give the SQ‐LNS and dispersible tablets were repeated monthly, while general feeding instructions were repeated irregularly. Daily reported adherence and disappearance rates were assessed in the whole IC. The sample size estimates were based on the number of children needed in each group to detect (with a significance of P 0.80) an effect size of >0.22 for diarrhoea incidence, malaria incidence and physical growth, assuming an attrition rate of 15%. The sample size estimate for change in PZC was based on an effect size of 0.6 and an attrition rate of 20%. For both 12‐h home observations and the 15‐month KAP interview, sample sizes of 10% and 20%, respectively, were chosen for convenience. Timing and frequency of data collection in both of the latter subsamples were chosen based on considerations of participant burden, cost constraints, and time needed for the data collection and quality control supervision. Field workers visited the children weekly for morbidity surveillance using standardised data collection tools and delivery of SQ‐LNS and tablets. In case of reported illnesses, treatment was provided free of charge for confirmed cases of malaria, non‐malaria fever and diarrhoea. At the same time, information on consumption of SQ‐LNS and dispersible tablets was collected by interviewing the mother or another adult caregiver (N = 2418) for the period since the previous home visit. Caregivers were asked to recall the child’s daily SQ‐LNS consumption (morning and afternoon, yes or no) and tablet consumption (yes or no). SQ‐LNS daily adherence was calculated by summing all consumption episodes each day. Any special case (e.g. SQ‐LNS/tablet served but not consumed or vomited) was recorded separately as a comment. To facilitate recall, a pictorial chart was distributed weekly, on which the caregivers were encouraged to record the consumption of SQ‐LNS/tablet and any morbidity symptoms each day, using simple tallying marks, which was used as memory aid during the interview. During the same weekly visit, field workers collected both empty and unused SQ‐LNS and tablet packages. The field workers recorded the number of unused packages as a proportion of the total distributed during the previous visit. This was done by estimating the percentage remaining in the cup or by counting the number of unused sachets for SQ‐LNS, and by counting the number of unused tablets. Daily disappearance rate was calculated as the difference between the distributed SQ‐LNS or tablets and the unused packages divided by the number of observation days. In a randomly selected subsample (N = 192), field workers spent 12 h in the family home on two occasions when the child was approximately 11 and 16 months of age to observe the child. Three data collectors were trained to collect the 12‐h home observation data unobtrusively. Caregivers were told that the main purpose of the observation was to record the child’s activity level. Data collectors emphasised upon arrival that the caregivers should not change their behaviour towards the child and should follow their usual routine. While present in the home, the data collectors also recorded the consumption of SQ‐LNS and dispersible tablets, breastfeeding, and feeding of other solid or liquid food. Field workers were trained not to show any particular interest in child feeding and/or SQ‐LNS and tablet consumption (e.g. not to move closer to examine the SQ‐LNS pot/sachet, the tablet or the child’s plate). During each home visit, the child was observed by two data collectors alternating the observations from 6 am to 6 pm and recording the relevant activities every 5 min using a standardised tool on a personal digital assistant (PDA, Hewlett‐Packard Development Company, L.P., Palo Alto, CA, USA). Child observations were carried out when the children’s general health status was reported as normal, and were rescheduled in case of illness. Information recorded about SQ‐LNS and dispersible tablet adherence included whether the supplement was served, the time of administration, the estimated amount consumed by the child, the way the products were offered (with food or alone) and any sharing with other family members. The consumed amounts of SQ‐LNS and tablets were calculated as the sum of all portions administered and consumed. At 15 months, a separate data collection team interviewed the child’s caregiver to assess the caregiver’s knowledge, attitude and practices related to complementary feeding (N = 349). KAP interviews were conducted by study personnel who were not involved in the distribution of SQ‐LNS or tablets, so less reporting bias might be expected during these interviews. In particular, caregivers were interviewed on: (1) SQ‐LNS consumption during the previous week; (2) SQ‐LNS consumption on the previous day; (3) acceptance of SQ‐LNS by the child and any reasons for non‐acceptance; (4) sharing of SQ‐LNS with other household members; and (5) method of serving the SQ‐LNS during the previous week (with any liquid or solid food). No information was collected on tablet consumption during these interviews on child feeding practices. Venous blood samples were collected from children in a randomly selected subgroup (N = 310) at enrollment (age 9 months) and after 9 months of intervention (age 18 months) using specimen collection and processing methods recommended by the International Zinc Nutrition Consultative Group (Brown et al. 2004). Children had to be reported free from fever and diarrhoea symptoms during the 2 days preceding the blood draw. At both time points, blood was drawn 1–2 h after the last breastfeeding episode. Blood was collected in trace element‐free, lithium heparin vacutainer tubes (Sarstedt AG & Co, Nümbrecht, Germany). Blood samples were stored on ice and transported to the field laboratory, where plasma was separated by centrifuging at 2800 rpm for 10 min and stored at −20°C until analyses. PZC was measured with inductively coupled plasma optical emission spectrophotometry (Vista; Varian Inc, Walnut Creek, CA, USA) at the Children’s Hospital of Oakland Research Institute (Killilea & Ames 2008; Wessells et al. 2012). Acute phase proteins (C‐reactive protein and α‐1‐acid glycoprotein) were analysed by enzyme‐linked immunosorbent assay (DBS‐Tech, Willstaett, Germany) (Erhardt et al. 2004) to adjust PZC for the effect of subclinical inflammation (Thurnham et al. 2010). Baseline data on maternal age, education level and marital status, number of children in the household, and data on household food insecurity access scale (Coates et al. 2007) were collected via interview for all study households within 2 weeks of enrollment. Children with less than 1 week of data collected (n = 17) were not included in the analysis. All the data were checked for consistency during cleaning and analysis. Inconsistent data were excluded based on pre‐defined criteria. Outcomes for the different adherence assessment methods (reported daily adherence and disappearance rate, 12‐h home observation, 15‐month KAP interview and adjusted PZC) were compared by study group using analysis of covariance for continuous outcome variables and logistic regression for categorical outcome variables. Additionally, outcomes for the 12‐h home observation were analysed using mixed model analysis to account for repeated measurements from the same subject. Group was used as the main effect, and age, initial PZC and sex as covariates for PZC analysis. All the analyses accounted for the random effect of the community, and for the family compound (i.e. concession) in case of daily reported adherence and disappearance rate. Group means were compared post hoc using least‐square means with the Tukey–Kramer test. Associations between reported daily adherence and disappearance rate, reported daily adherence and 12‐h home observation, and between reported daily adherence and 15‐month KAP interview of the same child and during the same observation day were calculated by non‐parametric Spearman correlation. Prevalence of reported non‐adherence and its association with illness days (fever, diarrhoea, malaria, vomiting, anorexia or hospitalisation) were analysed using mixed model adjusted for the random effect of the village and the concession. All statistical analyses were carried out using SAS software for Windows (9.3, SAS Institute, Cary, NC, USA).

Based on the provided information, here are some potential innovations that could improve access to maternal health:

1. Mobile Health (mHealth) Applications: Develop mobile applications that provide information and reminders to pregnant women and new mothers about prenatal care, nutrition, and postnatal care. These apps can also include features for tracking appointments, medication reminders, and connecting with healthcare providers.

2. Telemedicine: Implement telemedicine services to allow pregnant women in remote areas to consult with healthcare professionals through video calls or phone calls. This can help address the issue of limited access to healthcare facilities and specialists.

3. Community Health Workers: Train and deploy community health workers who can provide basic prenatal and postnatal care, as well as education on nutrition, breastfeeding, and hygiene practices. These workers can also help identify high-risk pregnancies and refer women to appropriate healthcare facilities.

4. Mobile Clinics: Set up mobile clinics that travel to rural and underserved areas to provide maternal health services, including prenatal check-ups, vaccinations, and health education. This can help overcome transportation barriers and bring healthcare services closer to the community.

5. Supply Chain Management: Improve supply chain management systems to ensure the availability of essential maternal health supplies, such as contraceptives, prenatal vitamins, and emergency obstetric care equipment. This can help prevent stockouts and ensure that women have access to the necessary resources for safe pregnancies and deliveries.

6. Health Education Programs: Develop and implement comprehensive health education programs that target women, families, and communities. These programs can focus on raising awareness about the importance of prenatal care, nutrition, family planning, and the benefits of skilled birth attendance.

7. Financial Incentives: Introduce financial incentives, such as conditional cash transfers or vouchers, to encourage pregnant women to seek prenatal care and deliver at healthcare facilities. This can help reduce financial barriers and increase access to quality maternal healthcare services.

8. Public-Private Partnerships: Foster collaborations between the public and private sectors to improve access to maternal health services. This can involve leveraging private healthcare providers, pharmacies, and technology companies to expand service delivery and reach more women in need.

9. Maternal Health Information Systems: Implement robust information systems to collect and analyze data on maternal health indicators, service utilization, and outcomes. This can help identify gaps in access and quality of care, inform decision-making, and monitor progress towards improving maternal health.

10. Policy and Advocacy: Advocate for policies and investments that prioritize maternal health and address the social determinants of health. This can include initiatives to improve healthcare infrastructure, strengthen health systems, and promote gender equality and women’s empowerment.

It is important to note that these recommendations are general and may need to be tailored to the specific context and challenges faced in improving access to maternal health in Burkina Faso.
AI Innovations Description
The recommendation to improve access to maternal health based on the provided information is to develop a more accurate and reliable method for assessing adherence to small-quantity lipid-based nutrient supplements (SQ-LNS) and dispersible tablets in community-based intervention trials. The current methods used, such as caregiver interviews and package return rates, have shown discrepancies in estimating adherence rates. This lack of accurate assessment can affect the interpretation of study outcomes and hinder the development of effective interventions.

To address this issue, it is recommended to explore innovative approaches for assessing adherence, such as the use of technology-based solutions. For example, mobile applications or electronic devices can be used to track and monitor the consumption of SQ-LNS and dispersible tablets in real-time. This would provide more accurate data on adherence rates and allow for immediate intervention if non-adherence is detected.

Additionally, incorporating objective measures of adherence, such as biomarkers or biological samples, can provide more reliable data on actual consumption. For example, measuring plasma zinc concentration can indicate the level of adherence to zinc tablets. This can be done through regular blood tests or the use of non-invasive methods, such as dried blood spot sampling.

Furthermore, it is important to consider the cultural and contextual factors that may influence adherence to maternal health interventions. Conducting qualitative research and engaging with the community can provide valuable insights into the barriers and facilitators of adherence. This information can then be used to tailor interventions and develop strategies to improve access to and utilization of maternal health services.

Overall, by developing innovative and accurate methods for assessing adherence and considering the contextual factors, access to maternal health can be improved, leading to better health outcomes for mothers and their children.
AI Innovations Methodology
To improve access to maternal health, here are some potential recommendations:

1. Mobile health (mHealth) interventions: Develop mobile applications or text messaging services to provide pregnant women with information on prenatal care, nutrition, and appointment reminders. This can help overcome barriers to accessing healthcare services, especially in remote areas.

2. Telemedicine: Implement telemedicine programs that allow pregnant women to consult with healthcare providers remotely. This can reduce the need for travel and provide timely access to medical advice and support.

3. Community health workers: Train and deploy community health workers to provide maternal health services in underserved areas. These workers can conduct prenatal visits, provide education on maternal health, and facilitate referrals to healthcare facilities when needed.

4. Maternal health clinics: Establish dedicated maternal health clinics that offer comprehensive services, including prenatal care, delivery, and postnatal care. These clinics can be strategically located in areas with limited access to healthcare facilities.

5. Transportation support: Provide transportation support for pregnant women to overcome geographical barriers. This can include arranging for ambulances or partnering with transportation services to ensure timely access to 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: Identify the specific population that will benefit from the innovation, such as pregnant women in a particular region or community.

2. Collect baseline data: Gather data on the current state of maternal health access in the target population. This can include information on the number of healthcare facilities, distance to the nearest facility, utilization rates, and health outcomes.

3. Develop a simulation model: Create a mathematical or computational model that represents the target population and simulates the impact of the recommendations. This model should consider factors such as population size, geographical distribution, healthcare infrastructure, and the proposed interventions.

4. Input intervention parameters: Specify the parameters of the recommended interventions, such as the number of mobile health users, the coverage of telemedicine services, the number of community health workers, or the availability of transportation support.

5. Run simulations: Use the simulation model to simulate the impact of the interventions over a specified time period. This can involve running multiple scenarios with different intervention parameters to assess their effectiveness.

6. Analyze results: Analyze the simulation results to evaluate the impact of the interventions on improving access to maternal health. This can include metrics such as the number of pregnant women reached, reduction in travel time, increase in healthcare utilization, and improvement in health outcomes.

7. Refine and iterate: Based on the simulation results, refine the intervention parameters and run additional simulations to optimize the impact. This iterative process can help identify the most effective combination of interventions for improving access to maternal health.

By using this methodology, policymakers and healthcare providers can assess the potential impact of different innovations and make informed decisions on implementing interventions to improve access to maternal health.

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