Minding the Micronutrient Data Gap

By Megan Bourassa, PhD, Program Lead for the Micronutrient Data Innovation Alliance, and Dr. Ken Brown, Distinguished Emeritus Professor, Department of Nutrition and Institute for Global Nutrition, University of California, Davis

The sparsity of data on micronutrient status is a critical limitation in estimating the prevalence of micronutrient deficiencies globally. For decades, the nutrition community has relied on the figure that two billion people are affected by micronutrient deficiencies. In fact, this figure is based on a 1991 World Health Organization (WHO) report that estimated the global prevalence of anemia, which is a poor predictor of micronutrient status.

The recent Lancet Global Health analysis by Stevens et al. demonstrates that two billion is likely a gross underestimation of the true burden, and it provides an important advancement in our understanding of the prevalence of micronutrient deficiencies (1). With this new analysis, we can more accurately state that globally more than half of preschool aged children (372 million) and two thirds of non-pregnant women of reproductive age (1.2 billion) have one or more micronutrient deficiencies. Unfortunately, the lack of sufficient data on micronutrient status prevented the group from making estimates for other population groups or for individual micronutrients.

Importantly, the Lancet Global Health analysis used data from just 22 countries, which is a major limitation that resulted in many extrapolations and assumptions about countries without data. Over a 20-year period (1998-2018), the WHO’s VMNIS database shows that 77 (56%) of low- and middle-income countries (LMICs) have data from preschool-aged children on vitamin A status (2,3). However, for other micronutrients like iron and zinc, this drops sharply with just 53 (38.4%) and 21 (15.2%) countries having data for preschool-aged children. Even less is known for other age groups and micronutrients, and very few countries in the database have conducted multiple surveys.

There are several reasons that investing in micronutrient data has been a challenge(4). Often, at the top of the list are the substantial financial implications of a nationally representative survey with nutrition biomarkers. Conducting MN surveys is further hindered by a lack of knowledge and awareness of the importance of having data at the country level. Many countries also lack the expertise to design surveys and analyze biological specimens, which can lead to additional challenges such as exporting samples for laboratory analysis. Surveys are typically done too infrequently to maintain local capacity, both in terms of trained individuals and laboratory equipment. However, having a strong political commitment with local champions and expertise are all enabling factors that can encourage more data collection on micronutrient status.

In 2020, the Micronutrient Forum released the Micronutrient Data Generation Strategic Plan to outline steps to increase the collection of micronutrient status data. The main recommendations from this plan include:

  • Greater advocacy on the importance of micronutrient data and dissemination of information on data collection methods.
  • Additional financial and technical support to countries for survey design, specimen collection and processing, laboratory analysis, as well as data analysis and interpretation for policy formulation.
  • Establishing regional resource labs and training hubs to increase the capacity for analyzing micronutrient biomarkers with external quality assessment to ensure specimens are analyzed in a standardized way and the analyses yield reliable results.
  • Developing an open access data repository with individual-level data to support periodic, systematic estimates of the global prevalence of micronutrient deficiencies.

One important suggestion in the strategic plan is the formation of a centralized funding mechanism for micronutrient data. Ideally, this would consist of a consortium of donors to support surveys and enhance laboratory capacity and training. This funding would be conditional upon several suggested national commitments, such as co-funding from national resources, use of standardized consensus laboratory analysis methods, , participation in external quality assurance programs, and presentation of individual-level data in an open access platform.

Following these steps for more and better data will ensure that future estimates of the burden of micronutrient deficiencies can be more accurate and comprehensive than those to date. While data are limited, recent surveys tend to include more micronutrients, which is an encouraging sign. With these data we can work towards better informed nutrition policies and programs that will support the health and development of populations worldwide.

References

  1. Stevens GA, Beal T, Mbuya MNN, Luo H, Neufeld LN. Micronutrient deficiencies among preschool-aged children and women of reproductive age worldwide: a pooled analysis of individual-level data from population-representative surveys. Published online 2022. www.thelancet.com/lancetghVol
  2. Brown KH, Moore SE, Hess SY, et al. Increasing the availability and utilization of reliable data on population micronutrient (MN) status globally: the MN Data Generation Initiative. Am J Clin Nutr. 2021;114(3):862-870. doi:10.1093/ajcn/nqab173
  3. World Health Organization. Micronutrient Database. Accessed January 30, 2023. https://platform.who.int/nutrition/micronutrients-database
  4. Manger MS, Brown KH, Osendarp SJM, Atkin RA, McDonald CM. Barriers to and Enablers of the Inclusion of Micronutrient Biomarkers in National Surveys and Surveillance Systems in Low-and Middle-Income Countries. Nutrients. 2022;14(10):2009.

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