Study on the Prevalence of Severe Anemia among Non-Pregnant Women of Reproductive Age in Rural China: A Large Population-Based Cross-Sectional Study

Nutrients. 2017 Nov 28;9(12):1298. doi: 10.3390/nu9121298.

Abstract

Globally, severe anemia impacts millions of non-pregnant women. However, studies on the prevalence of severe anemia through large epidemiologic surveys among non-pregnant women have been scarce in China. In this study, we aimed to study the prevalence of severe anemia and its determinants among non-pregnant women living in rural areas of China. Data were gathered for 712,101 non-pregnant women aged between 21 and 49 years who attended the 2012 National Free Preconception Health Examination Project. Severe anemia in non-pregnant women was defined as a hemoglobin (Hb) concentration lower than 80 g/L. Associated factors were analyzed using univariate and multivariate logistic regression methods. Out of the 712,101 non-pregnant women living in the rural areas of China, 1728 suffered from severe anemia, with a prevalence of 0.24% (95% confidence interval (CI): 0.23-0.25%). Results from the multivariable logistic regression showed that elderly (adjusted odds ratio (aOR) = 3.08), living in the northwest region (aOR = 2.88), having a history of anemia (aOR = 5.76), with heavy menstrual blood loss (aOR = 1.84), and with a history of using an intra-uterine device (aOR = 1.47) etc., were independent determinants for women with severe anemia in rural China. The prevalence of severe anemia among Chinese non-pregnant women living in the rural areas was lower than the reported global prevalence. Prevention and intervention programs for severe anemia are required among non-pregnant women of reproductive age in the rural areas of China.

Keywords: China; non-pregnant women; prevalence; rural areas; severe anemia.

MeSH terms

  • Adult
  • Anemia / epidemiology*
  • China / epidemiology
  • Cross-Sectional Studies
  • Female
  • Health Surveys*
  • Humans
  • Middle Aged
  • Odds Ratio
  • Prevalence
  • Risk Factors
  • Rural Population / statistics & numerical data*
  • Socioeconomic Factors