Maternal, newborn, child and adolescent health and ageing
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Indicator name:
Prevalence of anaemia in women aged 15-49, by pregnancy status (%) Short name:
Anaemia prevalence in women of reproductive age Data type:
Percentage Indicator Id:
4552
Topic:
Risk factors
Mortality and burden of disease
Rationale:
Anaemia is highly prevalent globally, disproportionately affecting children and women of reproductive age. Anaemia is associated with poor cognitive and motor development, and work capacity. Among pregnant women, iron deficiency anaemia is also associated with adverse reproductive outcomes such as preterm delivery, low-birth-weight infants, and decreased iron stores for the baby, which may lead to impaired development. Iron deficiency is considered the most common cause of anaemia but there are other nutritional and non-nutritional causes. Blood haemoglobin concentration is used to diagnose anaemia and it is affected by many factors, including altitude (metres above sea level), smoking, trimester of pregnancy, age and sex. When blood haemoglobin concentrations are used in combination with other indicators of iron status, they provide information about the severity of iron deficiency. The prevalence of anaemia in a population can be used to classify the public health significance of the problem. 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. Method of measurement
The anaemia status of women is assessed using blood haemoglobin concentrations. Blood haemoglobin concentrations are typically measured in surveys using the direct cyanmethemoglobin method in a laboratory or with a portable, battery-operated, haemoglobin photometer (using the azide-methaemoglobin method) in the field. M&E Framework:
Outcome
Method of estimation:
Prevalence of anaemia and/or mean haemoglobin in women of reproductive age were obtained from 412 population-representative data sources from 122 countries worldwide. Data collected from the years 1995 to 2023 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. Based on the latest evidence, the use of venous blood was recommended as the gold standard for measuring haemoglobin concentrations due to its high accuracy. However, thus far, national survey data based on venous blood are limited compared to capillary blood. For the current exercise, we accounted for possible higher error in haemoglobin measurements using capillary blood by taking only the mean haemoglobin concentrations because means are not affected by higher measurement errors. We used all available summary statistics or individual-level data if assessment was done using venous blood. We also allowed for suspected biased measurements by measurement method when using HemoCue® 301. These enhancements were applied considering the emerging evidence on measurement errors in haemoglobin that can influence the accuracy and precision of estimates.
Full details on statistical methods may be found here: National, regional, and global estimates of anaemia by severity in women and children for 2000–19: a pooled analysis of population-representative data (Stevens et al, 2022). https://www.thelancet.com/journals/langlo/article/PIIS2214-109X(22)00084-5/fulltext
Other possible data sources:
Surveillance systems; All references to Kosovo should be understood to be in the context of the United Nations Security Council resolution 1244 (1999)
Preferred data sources:
Population-based surveys
Unit Multiplier:
0
Expected frequency of data dissemination:
Every 2-3 years Expected frequency of data collection:
Data sources are continuously being collected from survey reports and manuscripts and entered into the WHO Micronutrients Database, part of the Vitamin and Mineral Nutrition Information Systems (VMNIS) Links:
For general questions or more information about this data portal, please contact mncahdata@who.int.