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Comprehending the patterns of ID burden is essential for developing targeted public health policies. Methods: Using data from the Global Burden of Disease (GBD) 2021 study for the years 1990\u20132021, the XGBoost model was constructed to predict prevalence and disability-adjusted life years (DALYs) for the period 2022\u20132050, based on key demographic variables. Shapley Additive exPlanations (SHAP) values were applied to interpret the contributions of each variable to the model\u2019s predictions. Additionally, the Age\u2013Period\u2013Cohort (APC) model was used to evaluate the effects of age, period, and birth cohort on both prevalence and DALYs. The relationship between the Socio-Demographic Index (SDI) and ID\u2019s age-standardized prevalence rate (ASPR) as well as the age-standardized DALYs rate (ASDR) was also analyzed to assess the influence of socioeconomic development on disease burden. Results: The global prevalent cases of ID grew from 984.61 million in 1990 to 1270.64 million in 2021 and are projected to reach 1439.99 million by 2050. Similarly, global DALYs from ID increased from 28.41 million in 1990 to 32.32 million in 2021, with a projected rise to 36.13 million by 2050. The ASPR declined from 18,204\/100,000 in 1990 to 16,433\/100,000 in 2021, with an estimated annual percentage change (EAPC) of \u22120.36% over this period. It is expected to decrease further to 15,922 by 2050, with an EAPC of \u22120.09% between 2021 and 2050. The ASDR was 518\/100,000 in 1990 and 424\/100,000 in 2021, with an EAPC of \u22120.68% from 1990 to 2021. It is expected to remain relatively stable at 419\/100,000 by 2050, with an EAPC of \u22120.02% between 2021 and 2050. In 2021, the highest ASPRs were recorded in Senegal (34,421\/100,000), Mali (34,233\/100,000), and Pakistan (33,942\/100,000). By 2050, Mali (35,070\/100,000), Senegal (34,132\/100,000), and Zambia (33,149\/100,000) are projected to lead. For ASDR, Yemen (1405\/100,000), Mozambique (1149\/100,000), and Mali (1093\/100,000) had the highest rates in 2021. By 2050, Yemen (1388\/100,000), Mali (1181\/100,000), and Mozambique (1177\/100,000) are expected to remain the highest. SHAP values demonstrated that gender was the leading predictor of ID, with age and year showing negative contributions. Females aged 10 to 60 consistently showed higher prevalence and DALYs rates compared to males, with the under-5 age group having the highest rates for both. Additionally, men aged 80 and above exhibited a rapid increase in prevalence. Furthermore, the ASPR and ASDR were significantly higher in regions with a lower SDI, highlighting the greater burden of ID in less developed regions. Conclusions: ID remains a significant global health concern, with its burden projected to persist through 2050, particularly in lower-SDI regions. Despite declines in ASPR and ASDR, total cases and DALYs are expected to rise. SHAP analysis revealed that gender had the greatest influence on the model\u2019s predictions, while both age and year showed overall negative contributions to ID risk. Children under 5, women under 60, and elderly men aged 80+ were the most vulnerable groups. These findings underscore the need for targeted interventions, such as improved nutrition, early screening, and addressing socioeconomic drivers through iron supplementation programs in low-SDI regions.<\/jats:p>","DOI":"10.3390\/nu16203434","type":"journal-article","created":{"date-parts":[[2024,10,10]],"date-time":"2024-10-10T07:53:05Z","timestamp":1728546785000},"page":"3434","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":35,"title":["Iron Deficiency: Global Trends and Projections from 1990 to 2050"],"prefix":"10.3390","volume":"16","author":[{"given":"Li","family":"Wang","sequence":"first","affiliation":[{"name":"Department of Medical Statistics, School of Public Health, Sun Yat-sen University, Guangzhou 510080, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Dan","family":"Liang","sequence":"additional","affiliation":[{"name":"Department of Immunology and Microbiology, College of Life Science and Technology, Jinan University, Guangzhou 510632, China"},{"name":"Guangdong Provincial Key Laboratory for Emergency Detection and Research on Pathogen of Emerging Infectious Disease, Guangdong Provincial Center for Disease Control and Prevention, Guangdong Workstation for Emerging Infectious Disease Control and Prevention, Guangzhou 511430, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Hengqian","family":"Huangfu","sequence":"additional","affiliation":[{"name":"Department of Medical Statistics, School of Public Health, Sun Yat-sen University, Guangzhou 510080, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Xinfu","family":"Shi","sequence":"additional","affiliation":[{"name":"Department of Medical Statistics, School of Public Health, Sun Yat-sen University, Guangzhou 510080, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Shuang","family":"Liu","sequence":"additional","affiliation":[{"name":"Department of Immunology and Microbiology, College of Life Science and Technology, Jinan University, Guangzhou 510632, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Panpan","family":"Zhong","sequence":"additional","affiliation":[{"name":"Department of Immunology and Microbiology, College of Life Science and Technology, Jinan University, Guangzhou 510632, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-1142-2845","authenticated-orcid":false,"given":"Zhen","family":"Luo","sequence":"additional","affiliation":[{"name":"Department of Immunology and Microbiology, College of Life Science and Technology, Jinan University, Guangzhou 510632, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0341-292X","authenticated-orcid":false,"given":"Changwen","family":"Ke","sequence":"additional","affiliation":[{"name":"Guangdong Provincial Key Laboratory for Emergency Detection and Research on Pathogen of Emerging Infectious Disease, Guangdong Provincial Center for Disease Control and Prevention, Guangdong Workstation for Emerging Infectious Disease Control and Prevention, Guangzhou 511430, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-4324-5465","authenticated-orcid":false,"given":"Yingsi","family":"Lai","sequence":"additional","affiliation":[{"name":"Department of Medical Statistics, School of Public Health, Sun Yat-sen University, Guangzhou 510080, China"},{"name":"Sun Yat-sen Global Health Institute, Sun Yat-sen University, Guangzhou 510080, China"},{"name":"Research Center of Health Informatics, Sun Yat-sen University, Guangzhou 510080, China"},{"name":"Guangdong Key Laboratory of Health Informatics, Guangzhou 510080, China"},{"name":"Guangzhou Joint Research Center for Disease Surveillance, Early Warning, and Risk Assessment, Guangzhou 510080, China"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2024,10,10]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1016\/S0098-2997(00)00006-6","article-title":"The roles of iron in health and disease","volume":"22","author":"Lieu","year":"2001","journal-title":"Mol. 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