Lower-middle-income economies vs Mauritania: Prevalence of anemia among women of reproductive age (15-49 years)

Lower-middle-income economies
43.8 %
in 2023
Mauritania
54.5 %
in 2023
Lower-middle-income economies rank
4th
Mauritania rank
3rd

Prevalence of anemia among women of reproductive age (15-49 years) over time

  • Lower-middle-income economies
  • Mauritania
0204060200020112023

How they compare

Mauritania currently reports 54.5 % against 43.8 % in Lower-middle-income economies, a difference of 10.7 %.

That makes Mauritania's figure about 1.2 times Lower-middle-income economies's.

Across all 24 years both countries report, Mauritania has been ahead every year.

Lower-middle-income economies ranks 4th and Mauritania ranks 3rd of 37 groups.

Mauritania has averaged higher in every one of the 3 decades both report.

Head to head by decade

Decade Lower-middle-income economies Mauritania Difference Ahead
2000s 43.02 % 55.57 % 12.55 % Mauritania
2010s 42.22 % 52.55 % 10.33 % Mauritania
2020s 43.22 % 53.73 % 10.5 % Mauritania

Averages of every year both report within each decade.

Frequently asked questions

Which has higher prevalence of anemia among women of reproductive age (15-49 years), Lower-middle-income economies or Mauritania?
Mauritania, at 54.5 % against 43.8 % in Lower-middle-income economies as of 2023.
What is the difference in prevalence of anemia among women of reproductive age (15-49 years) between Lower-middle-income economies and Mauritania?
10.7 %, with Mauritania ahead.
How many years of comparable data are there for Lower-middle-income economies and Mauritania?
24 years are reported by both, from 2000 to 2023.
How do Lower-middle-income economies and Mauritania rank globally for prevalence of anemia among women of reproductive age (15-49 years)?
Lower-middle-income economies ranks 4th and Mauritania ranks 3rd of 37 groups.
Where does this data come from?
Food and Agriculture Organization of the United Nations, published as Prevalence of anemia among women of reproductive age (15-49 years) (percent) — Value — Female — All age ranges or no breakdown by age — National. Statizoid refreshes it automatically from the source and publishes the full history for both places.

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Lower-middle-income economies vs Mauritania: Prevalence of anemia among women of reproductive age (15-49 years). Statizoid, drawing on Food and Agriculture Organization of the United Nations. Retrieved 18 September 2026, from https://economy.statizoid.com/compare/prevalence-of-anemia-among-women-of-reproductive-age-15-49-years-percent-value-female-all/lower-middle-income-economies/mauritania/

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<a href="https://economy.statizoid.com/compare/prevalence-of-anemia-among-women-of-reproductive-age-15-49-years-percent-value-female-all/lower-middle-income-economies/mauritania/">Lower-middle-income economies vs Mauritania: Prevalence of anemia among women of reproductive age (15-49 years)</a> — Statizoid

About this data

Indicator
Prevalence of anemia among women of reproductive age (15-49 years) (percent) — Value — Female — All age ranges or no breakdown by age — National
Unit
%
Source
Food and Agriculture Organization of the United Nations
Licence
CC BY-NC-SA 3.0 IGO (FAO)
Coverage
234 places, 5,616 data points, 2000–2023
Last refreshed

The Suite of Gender Indicators presents a set of indicators relevant to agrifood systems that are disaggregated by sex, with the aim of highlighting gender differences across agrifood systems. The initial set of indicators is based on those used in FAO’s 2023 Status of Women in Agrifood Systems (SWAFS) report and on the recommendations of an expert consultation held in December 2023, and covers key dimensions including economic participation, governance, agency, social norms, assets and services, education, health, and nutrition. Indicator selection was informed by expert judgment and by the availability of data with sufficient geographic and temporal coverage to enable meaningful comparisons across regions and over time. While most indicators are produced and published by FAO and other international organizations, the objective of this domain is to provide a one-stop shop for sex-disaggregated data on agrifood systems.