The Latin American and Caribbean region faces a severe malnutrition problem, including undernutrition, overweight and obesity: according to the latest FAO report (2023), the prevalence of overweight in children under 5 has increased in the last two decades and the reduction in the prevalence of stunting, which is at 11.5%, has slowed down in recent years. In Chile, this is a pressing problem: according to the Ministry of Health, 22.44% of children under 6 years of age monitored in the public health system have been diagnosed as overweight and 14.06% as obese.
Child malnutrition is a complex and multidimensional problem, so the search for strategies to address it must consider various aspects, ranging from physical conditions to the socioeconomic context of individuals. This requires quality information on multiple dimensions that is also easily accessible.
In response to this situation, Chile is implementing the Reduction of Child Malnutrition Project, the first longitudinal repository of integrated data for the study of child malnutrition and to guide public policy decisions in the country. This is a collective effort in which several entities are collaborating, including the Ministry of Health, the National Health Fund (FONASA), the Superintendence of Health, the National Board of School Aid and Scholarships (JUNAEB) and the National Commission for Evaluation and Productivity.
Currently, the repository contains information from 2012 to 2022, and we are working to update it annually and on a recurring basis. Its construction has not been without difficulties and has already generated several lessons learned. In this blog, we share the most important lessons.
Integrating Data to Address Malnutrition: Key Questions
1. Where do the main difficulties in integration arise from?
The main difficulties arise from legal and administrative barriers, not technological ones. The technological advances available to us that allow the operationalization of a repository such as this one are affordable and relatively easy to adapt. However, its implementation requires legal agreements and the adaptation of administrative processes, which can take considerable time. Raising the objective of reducing child malnutrition has been a good catalyst for these processes.
2. What are the key data to integrate?
Given that child malnutrition is a multidimensional problem, meaningful integration of data from various dimensions, such as nutrition, health, and sociodemographic data, is essential to capturing the complexity of this public health challenge. By putting children at the center, the concurrence of data for their characterization can be greatly enhanced.
3. Quality data or quantity data?
In the initial development phase of the repository, one of the keys was to make suitable data available, ensuring its reliability and relevance both for research and to support policy formulation. Improving data quality was a fundamental part of the project, so we identified this challenge as a priority for the next phase. Mainstreaming the objective of contributing to the reduction of child malnutrition has served to establish improved data quality as an important requirement for all institutions.
4. How to protect the privacy of children and families?
Once the data was collected, our focus was on protecting the privacy of individuals. This precaution allowed us to build a robust and ethical data repository. To achieve this, we implemented rigorous data protection and security measures through the adaptation of the “5 Safes” framework, which considers measures such as the Data Protection Impact Assessment (DPA) to identify and mitigate potential privacy risks. When making decisions that may affect children’s nutritional and health conditions, these safeguards become essential. Here, there may be a trade-off between the possibilities open to research and the safeguarding of privacy. Undoubtedly, a nominalized basis would broaden the scope of the tool. However, anonymization is part of the repository’s security measures.
5. A step-by-step process
Generating evidence on the factors that influence child malnutrition is at the basis of decision making to guide appropriate policies. We have yet to learn about the determinants of malnutrition, the economic costs associated with health service utilization, and the impact of specific interventions. That gives meaning to these data integration efforts.
Childhood Malnutrition and Data Use: Lessons Learned
This project taught us that database integration goes beyond technology: it requires a clear policy objective that calls participating entities to action. In addition, it has been key to work with a deep commitment to privacy protection and clear communication between all parties.
Creating an integrated data repository to comprehensively characterize the child population and address malnutrition is a complex but achievable process. By focusing on data quality, safety, and inter-institutional collaboration, we are better prepared to meet this important public health challenge and work towards a healthier future for Chile’s children.
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