Indicator 2.2.3 Prevalence of anaemia in women aged 15 to 49 years, by pregnancy status (percentage)

Indicator 2.2.3: Prevalence of anaemia in women aged 15 to 49 years, by pregnancy status (percentage)

Target 2.2: By 2030, end all forms of malnutrition, including achieving, by 2025, the internationally agreed targets on stunting and wasting in children under 5 years of age, and address the nutritional needs of adolescent girls, pregnant and lactating women and older persons

World Health Organization (WHO)

Definition:

Percentage of women aged 15−49 years with a haemoglobin concentration less than 120 g/L for non-pregnant women and lactating women, and less than 110 g/L for pregnant women, adjusted for altitude and smoking.

Concepts:

Anaemia: condition in which the concentration of blood haemoglobin concentration falls below established cut-off values.

Iron deficiency: state in which there is insufficient iron to maintain the normal physiological function of blood, brain and muscles (ICD-11, 5B5K.0 iron deficiency)

Iron deficiency anaemia: (ICD-11, 3A00, iron deficiency anaemia)

Blood haemoglobin concentration: concentration of haemoglobin in whole blood

Percent (%)

The preferable source of data is population-based surveys. Data from surveillance systems may be used under some conditions, but recorded diagnoses are typically underestimated. Data are from the Micronutrients Database of the WHO Vitamin and Mineral Nutrition Information System (VMNIS) (https://www.who.int/teams/nutrition-and-food-safety/databases/vitamin-and-mineral-nutrition-information-system This database compiles and summarizes data on the micronutrient status of populations from various other sources, including data collected from the scientific literature and through collaborators, including WHO regional and country offices, United Nations organizations, ministries of health, research and academic institutions, and nongovernmental organizations. In addition, anonymized individual-level data are obtained from multi-country surveys, including demographic and health surveys, multiple indicator cluster surveys, reproductive health surveys and malaria indicator surveys.

There are two main data sources of survey data for anaemia: 1) reports generated by countries or implementing partners and 2) published manuscripts. Occasionally, Member States, regional offices, the international community or colleagues managing other databases within WHO provide reports directly to staff responsible for maintaining the WHO Micronutrients Database. If data meet the eligibility criteria, they are entered into the database. Reports and publications are primarily requested and collected from:

• Ministries of Health through WHO regional and country offices,
• National research and academic institutions,
• Nongovernmental organizations, and
• Organizations of the United Nations system.

Despite the extensive data search, data for blood haemoglobin concentrations are still limited, compared to other nutritional indicators such as child anthropometry (1, 24); this was especially true in the high-income countries of the WHO European Region. As a result, the estimates may not capture the full variation across countries and regions, tending to “shrink” towards global means when data are sparse.

Estimates may differ from those reported by countries.

Prevalence of anaemia and/or mean haemoglobin in women of reproductive age were obtained from 408 population-representative data sources from 124 countries worldwide. Data collected from 1995 to 2020 were used. Adjustment of data on blood haemoglobin concentrations for altitude and smoking was carried out whenever possible. Biologically implausible haemoglobin values (<25 g/L or >200 g/L) were excluded. A Bayesian hierarchical mixture model was used to estimate haemoglobin distributions and systematically addressed missing data, non-linear time trends, and representativeness of data sources.

Full details on statistical methods may be found here: Global, regional, and national trends in haemoglobin concentration and prevalence of total and severe anaemia in children and pregnant and non-pregnant women for 1995–2011: a systematic analysis of population-representative data (Stevens et al, 2013).

Briefly, the model calculates estimates for each country and year, informed by data from that country and year themselves, if available, and by data from other years in the same country and in other countries with data for similar time periods, especially countries in the same region. The model borrows data, to a greater extent, when data are non-existent or weakly informative, and to a lesser degree for data-rich countries and regions. The resulting estimates are also informed by covariates that help predict blood haemoglobin concentrations (e.g. socio-demographic index, meat supply (kcal/capita), mean BMI for women and log of under-five mortality for children). The uncertainty ranges (credibility intervals) reflect the major sources of uncertainty, including sampling error, non-sampling error due to issues in sample design/measurement, and uncertainty from making estimates for countries and years without data.

2024-07-29

World Health Organization (WHO)

Anaemia is estimated to contribute to 17% lower productivity in heavy manual labour and 5% lower productivity in other manual labour (Goal 1 End poverty in all its forms everywhere); during pregnancy, it increases the risk of maternal and perinatal mortality and contributes to low birth-weight infants (Goal 3. Good health and well-being); it also limits cognitive development, children who have adequate iron have more energy to participate in classroom exercises, and they are more mentally prepared to master the material (Goal 4. Quality education); anaemia rates in females are much higher than males — while anaemia rates decrease for males by the end of puberty, they remain high for females through reproductive years due to menstruation, thus reducing anaemia contributes to boosting females’ relative academic performance and worker productivity and helps achieve gender equality (Goal 5. Gender equality).