BACKGROUND: Micronutrient malnutrition is a public health problem in many developing countries. Its negative impact on income growth is recognized in principle, but there are widely varying estimates of the related economic cost. OBJECTIVE: To discuss available studies that quantify the cost of micronutrient malnutrition, and to develop an alternative framework and apply it to India. METHODS: Detailed burden of disease calculations are used to estimate the economic cost of micronutrient malnutrition based on disability-adjusted life years (DALYs) lost. RESULTS: The short-term economic cost of micronutrient malnutrition in India amounts to 0.8% to 2.5% of the gross domestic product. CONCLUSIONS: Although the results confirm that micronutrient malnutrition is a huge economic problem, the estimates are lower than those of most previous studies. The differences may be due to differences in underlying assumptions, quality of data, and precision of calculation, but also to dynamic interactions between nutrition, health, and economic productivity, which are difficult to capture. Clear explanation of all calculation details would be desirable for future studies in order to increase credibility and transparency.
BACKGROUND: Micronutrient malnutrition is a public health problem in many developing countries. Its negative impact on income growth is recognized in principle, but there are widely varying estimates of the related economic cost. OBJECTIVE: To discuss available studies that quantify the cost of micronutrient malnutrition, and to develop an alternative framework and apply it to India. METHODS: Detailed burden of disease calculations are used to estimate the economic cost of micronutrient malnutrition based on disability-adjusted life years (DALYs) lost. RESULTS: The short-term economic cost of micronutrient malnutrition in India amounts to 0.8% to 2.5% of the gross domestic product. CONCLUSIONS: Although the results confirm that micronutrient malnutrition is a huge economic problem, the estimates are lower than those of most previous studies. The differences may be due to differences in underlying assumptions, quality of data, and precision of calculation, but also to dynamic interactions between nutrition, health, and economic productivity, which are difficult to capture. Clear explanation of all calculation details would be desirable for future studies in order to increase credibility and transparency.
Authors: Reem Joukhadar; Rebecca Thistlethwaite; Richard M Trethowan; Matthew J Hayden; James Stangoulis; Suong Cu; Hans D Daetwyler Journal: Theor Appl Genet Date: 2021-07-12 Impact factor: 5.699
Authors: Simon Wieser; Rafael Plessow; Klaus Eichler; Olivia Malek; Mario V Capanzana; Imelda Agdeppa; Urs Bruegger Journal: BMC Public Health Date: 2013-12-11 Impact factor: 3.295
Authors: Rachel Hurst; Edwin W P Siyame; Scott D Young; Allan D C Chilimba; Edward J M Joy; Colin R Black; E Louise Ander; Michael J Watts; Benson Chilima; Jellita Gondwe; Dalitso Kang'ombe; Alexander J Stein; Susan J Fairweather-Tait; Rosalind S Gibson; Alexander A Kalimbira; Martin R Broadley Journal: Sci Rep Date: 2013 Impact factor: 4.379