Getting back on track to meet global anaemia reduction targets: a Lancet Haematology Commission

Abstract

Global Burden and Data Gaps: Many countries lack reliable data on anaemia prevalence, especially for populations beyond young children and women of reproductive age. Few national surveys measure both anaemia and its underlying causes. We call for the creation of a standardised global data repository and the development of a harmonised micronutrient survey platform to collect comprehensive, periodic data. We also recommend better integration of data across sources, including household surveys and other health data sources, and inclusion of haemoglobin assessment in existing survey platforms that already collect venous blood. Continued financial support and coordination of demographic and health surveys are crucial, especially in light of potential reductions in U.S. funding for global data initiatives.

Anaemia Aetiology and Management: The causes of anaemia are multifactorial including iron deficiency, other micronutrient deficiencies, infections, inflammation, blood loss, and inherited blood disorders. We identify critical knowledge gaps in the complex interactions between these risk factors across life stages in different populations.

We recommend targeted research to elucidate underlying mechanisms, improved tools for assessing anaemia determinants, advanced nutritional interventions, and integration of infection control with nutrition programs. Specific areas highlighted for further research include optimising iron dosing and formulations, effective combinations of micronutrients, improving fortification and biofortification strategies, and evaluating non-nutritional interventions such as delayed cord clamping and infection control, and management of heavy menstrual bleeding and post-partum haemorrhage. We also emphasise the need to address environmental factors contributing to anaemia, such as air pollution and climate change.

Implementation and Governance: Effective implementation of anaemia control programs requires tailored, multi-sectorial strategies and ongoing monitoring. Our key recommendations for effective implementation of anaemia reduction programmes are: (1) developing clear governance structures at global, national and sub-national levels to ensure proper oversight and accountability; (2) broadening national nutrition plans to incorporate cross-sector coordination and efficient management of anaemia-related strategies, and (3) placing social equity and fundamental human rights at the centre of anaemia-focused policies and interventions.

Redefining Future Anaemia Reduction Targets: This Commission critically evaluates the process by which the 2030 anaemia targets were set and proposes a more evidence-based, context-specific approach. Key limitations of the current 50% anaemia reduction target are: (1) not clearly accounting for country-specific contexts; (2) focussing on overall prevalence of anaemia rather than anaemia disease burden; and (3) a reduction target for magnitude that was unachievable using available interventions even if maximally deployed.

We proposed a novel target-setting framework based on health economic modelling. This approach incorporates national anaemia prevalence, current intervention coverage and effectiveness, potential scale-up costs, and a range of potential country-specific cost-effectiveness thresholds. This approach aims to balance ambition with achievability while maintaining a unified global vision. Preliminary application of this method suggests a global summary target of 12–22% reduction in anaemia prevalence, significantly lower than the current 50% target, with marked variation in country-specific targets. We advocate for a participatory, iterative target-setting process aligning with local priorities and resources.

Conclusion: Reducing the burden of anaemia requires a comprehensive, multi-sectorial approach that considers its complex aetiology and varied impacts across populations. By adopting the recommendations outlined in this Commission—including improved data systems, more targeted research, integrated programme implementation, and evidence-based target-setting—the global health community can renew momentum toward meaningful anaemia reduction. Achieving progress will require sustained political commitment, increased investment, and coordinated action from governments, international agencies, civil society, and researchers. As the global health agenda evolves beyond the 2030 Sustainable Development Goals, the insights and strategies presented in this Commission offer a roadmap for a more effective, equitable, and sustainable approach to tackling anaemia worldwide.

Figure 1:. Global Progress towards anaemia targets in women 1990–2021.

Shaded area encloses the estimated overall change in the prevalence of anaemia in women of reproductive age, in all countries, as estimated by the Global Burden of Disease (GBD) study. Individual lines show the specific trajectories of eight select countries. All lines are shown relative to the mean prevalence of anaemia during the baseline period (1993–2005). That is, from the perspective of the Sustainable Development Goals (SDGs) Target Indicator 2·2·3 for anaemia. The horizontal dashed line shows the SDGs and Global Nutrition Targets (GNTs) goal of a 50% reduction in prevalence.

Figure 2:

Conceptual framework of anaemia and its drivers

Figure 3:. Prevalence of any anaemia in 2019 and data gaps in young children, non-pregnant women, and pregnant women according to WHO

Key (for prevalence): 60, 40, 20, NA; Key (for gaps): No anaemia data; At least one source; Three or more sources; For prevalence: Haemoglobin, Hb. Any anaemia is defined as Hb <110 g/L in children aged 6–59 months; Hb <120 g/L in non-pregnant women aged 15–49 years; Hb <110 g/L in pregnant women aged 15–49 years. Data estimates derived from Stevens et al. 2022. Estimates are not yet available based on updated WHO haemoglobin thresholds and adjustments. For gaps: Data from the Vitamin and Mineral Nutrition Information System (VMNIS) between 2000–2020. Age intervals are defined based on WHO’s VMNIS classification of population groups and do not exactly cover the age ranges of interest: preschool aged children (i.e. young children) 0–75 months, non-pregnant women 12–60 years, and pregnant women 10–54 years. The most common age grouping for each population is 6–59 months for young children (77%), 15–49 years for non-pregnant women (87%), 15–49 years for pregnant women (53%).

Figure 3:. Prevalence of any anaemia in 2019 and data gaps in young children, non-pregnant women, and pregnant women according to WHO

Key (for prevalence): 60, 40, 20, NA; Key (for gaps): No anaemia data; At least one source; Three or more sources; For prevalence: Haemoglobin, Hb. Any anaemia is defined as Hb <110 g/L in children aged 6–59 months; Hb <120 g/L in non-pregnant women aged 15–49 years; Hb <110 g/L in pregnant women aged 15–49 years. Data estimates derived from Stevens et al. 2022. Estimates are not yet available based on updated WHO haemoglobin thresholds and adjustments. For gaps: Data from the Vitamin and Mineral Nutrition Information System (VMNIS) between 2000–2020. Age intervals are defined based on WHO’s VMNIS classification of population groups and do not exactly cover the age ranges of interest: preschool aged children (i.e. young children) 0–75 months, non-pregnant women 12–60 years, and pregnant women 10–54 years. The most common age grouping for each population is 6–59 months for young children (77%), 15–49 years for non-pregnant women (87%), 15–49 years for pregnant women (53%).

Figure 3:. Prevalence of any anaemia in 2019 and data gaps in young children, non-pregnant women, and pregnant women according to WHO

Key (for prevalence): 60, 40, 20, NA; Key (for gaps): No anaemia data; At least one source; Three or more sources; For prevalence: Haemoglobin, Hb. Any anaemia is defined as Hb <110 g/L in children aged 6–59 months; Hb <120 g/L in non-pregnant women aged 15–49 years; Hb <110 g/L in pregnant women aged 15–49 years. Data estimates derived from Stevens et al. 2022. Estimates are not yet available based on updated WHO haemoglobin thresholds and adjustments. For gaps: Data from the Vitamin and Mineral Nutrition Information System (VMNIS) between 2000–2020. Age intervals are defined based on WHO’s VMNIS classification of population groups and do not exactly cover the age ranges of interest: preschool aged children (i.e. young children) 0–75 months, non-pregnant women 12–60 years, and pregnant women 10–54 years. The most common age grouping for each population is 6–59 months for young children (77%), 15–49 years for non-pregnant women (87%), 15–49 years for pregnant women (53%).

Figure 3:. Prevalence of any anaemia in 2019 and data gaps in young children, non-pregnant women, and pregnant women according to WHO

Key (for prevalence): 60, 40, 20, NA; Key (for gaps): No anaemia data; At least one source; Three or more sources; For prevalence: Haemoglobin, Hb. Any anaemia is defined as Hb <110 g/L in children aged 6–59 months; Hb <120 g/L in non-pregnant women aged 15–49 years; Hb <110 g/L in pregnant women aged 15–49 years. Data estimates derived from Stevens et al. 2022. Estimates are not yet available based on updated WHO haemoglobin thresholds and adjustments. For gaps: Data from the Vitamin and Mineral Nutrition Information System (VMNIS) between 2000–2020. Age intervals are defined based on WHO’s VMNIS classification of population groups and do not exactly cover the age ranges of interest: preschool aged children (i.e. young children) 0–75 months, non-pregnant women 12–60 years, and pregnant women 10–54 years. The most common age grouping for each population is 6–59 months for young children (77%), 15–49 years for non-pregnant women (87%), 15–49 years for pregnant women (53%).

Figure 3:. Prevalence of any anaemia in 2019 and data gaps in young children, non-pregnant women, and pregnant women according to WHO

Key (for prevalence): 60, 40, 20, NA; Key (for gaps): No anaemia data; At least one source; Three or more sources; For prevalence: Haemoglobin, Hb. Any anaemia is defined as Hb <110 g/L in children aged 6–59 months; Hb <120 g/L in non-pregnant women aged 15–49 years; Hb <110 g/L in pregnant women aged 15–49 years. Data estimates derived from Stevens et al. 2022. Estimates are not yet available based on updated WHO haemoglobin thresholds and adjustments. For gaps: Data from the Vitamin and Mineral Nutrition Information System (VMNIS) between 2000–2020. Age intervals are defined based on WHO’s VMNIS classification of population groups and do not exactly cover the age ranges of interest: preschool aged children (i.e. young children) 0–75 months, non-pregnant women 12–60 years, and pregnant women 10–54 years. The most common age grouping for each population is 6–59 months for young children (77%), 15–49 years for non-pregnant women (87%), 15–49 years for pregnant women (53%).

Figure 3:. Prevalence of any anaemia in 2019 and data gaps in young children, non-pregnant women, and pregnant women according to WHO

Key (for prevalence): 60, 40, 20, NA; Key (for gaps): No anaemia data; At least one source; Three or more sources; For prevalence: Haemoglobin, Hb. Any anaemia is defined as Hb <110 g/L in children aged 6–59 months; Hb <120 g/L in non-pregnant women aged 15–49 years; Hb <110 g/L in pregnant women aged 15–49 years. Data estimates derived from Stevens et al. 2022. Estimates are not yet available based on updated WHO haemoglobin thresholds and adjustments. For gaps: Data from the Vitamin and Mineral Nutrition Information System (VMNIS) between 2000–2020. Age intervals are defined based on WHO’s VMNIS classification of population groups and do not exactly cover the age ranges of interest: preschool aged children (i.e. young children) 0–75 months, non-pregnant women 12–60 years, and pregnant women 10–54 years. The most common age grouping for each population is 6–59 months for young children (77%), 15–49 years for non-pregnant women (87%), 15–49 years for pregnant women (53%).

Figure 4:. A) Comparison of anaemia prevalence (%) between the new and old cutoffs and altitude adjustment among children aged 6–59 months in the African region. B) Comparison of anaemia prevalence (%) between the old and new altitude and smoking adjustment among non-pregnant women aged 15–49 years in the African region.

New cutoff defined as Hb<105 g/L for children aged 6–23 months and Hb<110 g/L for children aged 24–59 months; Old cutoff defined as Hb<110 g/L for children aged 6–59 months. New altitude adjustment defined as Hb adjustment (g/L) = (0·0056384 x elevation in meters) + (0·0000003 x elevation in meterŝ2); Old altitude adjustment defined as Hb adjustment (g/L) = − 0·32 x (0·0032808 x elevation in meters) + 0·22 x (0·0032808 x elevation in meters)^2. New smoking adjustment defined as Hb adjustment (g/L) = (0·4565 x cigarette number per day) + (−0·0078 x cigarette number^2). Old smoking adjustment defined by number of cigarettes per day: <10 (no adjustment), 10–19 (−3 g/L), 20–39 (−5 g/L), 40 or more (−7 g/L), unknown quantity or non-cigarettes smoking (−3 g/L). Sample was limited to the legally recognised resident population. Countries were selected based on the highest percentage of the population residing at different altitudes. If two countries met the criteria, one was selected randomly. If the same country had the highest percentage of the population at consecutive altitude bins, the altitude bins were combined. Data was restricted to countries with publicly available microdata for children and women.

Figure 4:. A) Comparison of anaemia prevalence (%) between the new and old cutoffs and altitude adjustment among children aged 6–59 months in the African region. B) Comparison of anaemia prevalence (%) between the old and new altitude and smoking adjustment among non-pregnant women aged 15–49 years in the African region.

New cutoff defined as Hb<105 g/L for children aged 6–23 months and Hb<110 g/L for children aged 24–59 months; Old cutoff defined as Hb<110 g/L for children aged 6–59 months. New altitude adjustment defined as Hb adjustment (g/L) = (0·0056384 x elevation in meters) + (0·0000003 x elevation in meterŝ2); Old altitude adjustment defined as Hb adjustment (g/L) = − 0·32 x (0·0032808 x elevation in meters) + 0·22 x (0·0032808 x elevation in meters)^2. New smoking adjustment defined as Hb adjustment (g/L) = (0·4565 x cigarette number per day) + (−0·0078 x cigarette number^2). Old smoking adjustment defined by number of cigarettes per day: <10 (no adjustment), 10–19 (−3 g/L), 20–39 (−5 g/L), 40 or more (−7 g/L), unknown quantity or non-cigarettes smoking (−3 g/L). Sample was limited to the legally recognised resident population. Countries were selected based on the highest percentage of the population residing at different altitudes. If two countries met the criteria, one was selected randomly. If the same country had the highest percentage of the population at consecutive altitude bins, the altitude bins were combined. Data was restricted to countries with publicly available microdata for children and women.

Figure 5:. Haemoglobin measurement technique by region.

Data from the Vitamin and Mineral Nutrition Information System (VMNIS) between 2000–2020.

Figure 6:. Continuous 5th centile haemoglobin thresholds in males (red) and females (blue) across the life course (6 months to 65 years)

Using datasets from the Australian Health Survey-AHS (adults aged 18 to 65 years in Australia), China Health and Nutrition Survey-CHNS (adults aged 18–65 years in China) Applied Research Group for Kids-TARGet Kids! (children aged 6 months to 11 years in Canada), Benefits and Risks of Iron interventions in Children-BRISC (children aged 11 months in Bangladesh), Encuesta Nacional de Salud y Nutrición-ENSANUT (children aged 6 to 59 months in Ecuador), Generation R study (pregnant women aged 18 to 45 years in the Netherlands), Health Survey for England-HSE (Adults aged 18 to 65 years in England) and National Health and Nutrition Examination Survey-NHANES (children and adults aged 6 months to 65 years in USA). The pooled continuous centiles and confidence intervals across data sources were estimated without accounting for the complex survey and weighting. Figure reproduced with permission from Bratt et al. (2024).

Figure 7:. Overview of current interventions addressing anaemia.

On the left are clinical interventions targeting individuals; in the middle are interventions aimed at vulnerable sub-populations, such as women of reproductive age, young children, or those in high-burden infection settings; and on the right are systemic or environmental interventions designed to benefit whole populations.

Figure 8:. Nationally tailored anaemia reduction targets, and global summary targets, under different potential cost-effectiveness thresholds (CETs).

Each panel presents the anaemia reduction targets for 191 countries, colour-coded by income level. Grey line indicates the global summary target; light grey shaded region encloses 95% of global targets across Monte Carlo simulations. Panel A: With a CET of 1 x gross domestic product (GDP)/capita, the global summary target is 17%, with national targets ranging from 0% to ~30%. Panel B: Under a lower CET that approximates an opportunity-cost based approach, the global summary target decreases to 12%, with national targets also ranging from 0% to ~30%. Panel C: When cost constraints are removed, the global summary target rises to 22%, with national targets ranging from ~5% to ~35%. In all scenarios, the global summary targets remain well below the 50% target set by the SDGs and GNTs.

Figure 8:. Nationally tailored anaemia reduction targets, and global summary targets, under different potential cost-effectiveness thresholds (CETs).

Each panel presents the anaemia reduction targets for 191 countries, colour-coded by income level. Grey line indicates the global summary target; light grey shaded region encloses 95% of global targets across Monte Carlo simulations. Panel A: With a CET of 1 x gross domestic product (GDP)/capita, the global summary target is 17%, with national targets ranging from 0% to ~30%. Panel B: Under a lower CET that approximates an opportunity-cost based approach, the global summary target decreases to 12%, with national targets also ranging from 0% to ~30%. Panel C: When cost constraints are removed, the global summary target rises to 22%, with national targets ranging from ~5% to ~35%. In all scenarios, the global summary targets remain well below the 50% target set by the SDGs and GNTs.

Figure 8:. Nationally tailored anaemia reduction targets, and global summary targets, under different potential cost-effectiveness thresholds (CETs).

Each panel presents the anaemia reduction targets for 191 countries, colour-coded by income level. Grey line indicates the global summary target; light grey shaded region encloses 95% of global targets across Monte Carlo simulations. Panel A: With a CET of 1 x gross domestic product (GDP)/capita, the global summary target is 17%, with national targets ranging from 0% to ~30%. Panel B: Under a lower CET that approximates an opportunity-cost based approach, the global summary target decreases to 12%, with national targets also ranging from 0% to ~30%. Panel C: When cost constraints are removed, the global summary target rises to 22%, with national targets ranging from ~5% to ~35%. In all scenarios, the global summary targets remain well below the 50% target set by the SDGs and GNTs.