Iron Deficiency and Iron‐Deficiency Anemia Among Reproductive‐Age Women in the United States: Prevalence and Disparities, 2015–2023

Overweight/Obesity and Body Fat Percentage in Relation to Iron Status Among Indonesian Women of Reproductive Age: Evidence from a Case–Control Study

Background/Objectives: Obesity-related inflammation may disrupt iron homeostasis and increase the risk of iron deficiency, yet evidence among women in low- and middle-income countries remains limited. This study examined the independent association between overweight/obesity and iron status among Indonesian women of reproductive age. Methods: A case–control study was conducted among 340 nonpregnant women aged 20–29 years in Surabaya, Indonesia. Sociodemographic, dietary, menstrual, and anthropometric data were collected alongside venous blood samples. Logistic regression models were used to examine associations between adiposity measures and iron deficiency (ID), anaemia, and iron deficiency anaemia (IDA), adjusting for potential confounders. Results: Inflammation-adjusted serum ferritin was significantly higher among women with overweight/obesity than among normal-weight women (22.39 ± 21.7 vs. 17.78 ± 17.6 µg/L; p = 0.033). Consistent with this, the prevalence of ID was lower among women with overweight/obesity, likely reflecting inflammation-related ferritin elevation that may influence diagnostic classification. BMI-defined overweight/obesity was not independently associated with ID, anaemia, or IDA. In contrast, higher body fat percentage was inversely associated with ID (AOR 0.93; 95% CI 0.86, 0.99) and IDA (AOR 0.86; 95% CI 0.75, 0.99). Elevated alpha-1-acid glycoprotein (AGP) was independently associated with higher odds of IDA, and menstrual iron loss was an independent predictor of anaemia and IDA. Conclusions: BMI alone is insufficient to capture the relationship between adiposity and iron status in women of reproductive age. Body fat percentage appears to be a more sensitive indicator of adiposity-related iron risk. These findings suggest that inflammation associated with adiposity may alter iron biomarkers, and reliance on BMI alone may obscure the true burden of iron deficiency in this population.

Postpartum anemia in India within 6 months of delivery: Prevalence, socioeconomic inequalities, and regional disparities: A secondary analysis of NFHS-5 (Fifth National Family Health Survey, 2019-2021).

OBJECTIVE To estimate the prevalence and severity of postpartum anemia among Indian women within 6 months of delivery and identify associated socioeconomic, healthcare, and geographic factors. METHODS This cross-sectional secondary analysis used data from NFHS-5 (Fifth National Family Health Survey, 2019-2021). Women aged 15 to 49 years who had a live birth within 6 months before the survey, were not pregnant at interview, and had hemoglobin measurements were included. Postpartum anemia was defined as hemoglobin <11.0 g/dL. Survey-weighted prevalence estimates were calculated, and associated factors were examined using survey-weighted Poisson regression with robust variance to estimate adjusted prevalence ratios (aPRs) and 95% confidence intervals (CIs). RESULTS Among 24 700 postpartum women, the prevalence of postpartum anemia was 34.7%. Mild, moderate, and severe anemia affected 19.1%, 14.7%, and 0.9% of women, respectively. Prevalence declined from 38.1% during the first 2 months postpartum to 31.3% at 5 to 6 months. Higher prevalence was observed among women with no education (aPR 1.25 [95% CI, 1.13-1.39]), those in the poorest wealth quintile (aPR, 1.19 [95% CI, 1.06-1.35]), Scheduled Tribe women (aPR, 1.21 [95% CI, 1.11-1.31]), underweight women (aPR, 1.11 [95% CI, 1.05-1.17]), and women who delivered at home (aPR, 1.15 [95% CI, 1.08-1.22]). Geographic disparities were evident, with higher prevalence in eastern, northeastern, and central India. CONCLUSION One in three Indian women experiences postpartum anemia within 6 months of childbirth. Strengthening postpartum screening, nutrition support, and targeted maternal health interventions may reduce disparities and improve maternal health outcomes.

Prevalence and Determinants of Iron Deficiency Anemia Among Pregnant Women and Adolescent Girls

Anemia among women of reproductive age is one of India's most persistent nutritional problems, and its burden is not spread evenly across the country. Bihar and Uttar Pradesh, two of the most populous states, record some of the highest rates, yet few studies examine pregnant women and adolescent girls side by side in these settings. This study estimated anemia prevalence and identified its determinants in both groups. We analysed cross-sectional data from the fifth round of the National Family Health Survey (2019 to 2021), covering 4,847 pregnant women and 21,358 adolescent girls aged 15 to 19 years. Anemia was classified using standard haemoglobin thresholds measured from capillary blood, and multivariable logistic regression assessed associated factors. Anemia affected 63.1 percent of pregnant women in Bihar and 50.4 percent in Uttar Pradesh; among adolescent girls the figures were 63.5 and 49.8 percent. Low maternal education, the poorest wealth quintile, Scheduled Caste or Tribe membership, rural residence, higher parity, and short birth spacing carried higher odds of anemia. Coverage of iron and folic acid supplementation stayed low in both states. The findings support state-specific programmes that reach girls well before they become pregnant.

Anemia and Iron Deficiency Anemia in Saudi Arabia: A Systematic Review of Prevalence and Contributing Factors

Background: Iron deficiency anemia (IDA) is among the most prevalent nutritional disorders worldwide and a growing public health concern among women in Saudi Arabia. Available Saudi evidence remains fragmented, with single-center studies that vary by population, region, and diagnostic criteria. This review evaluated the prevalence of anemia in Saudi Arabia, assessed gender-related differences across the lifespan, and highlighted local determinants and prevention strategies relevant to women. Methods: Eight cross-sectional studies (26,412 participants) reporting anemia prevalence in Saudi individuals aged ≥13 with both-sex data were identified across five databases (2007–2024), excluding chronic-disease and under-13 studies. Quality was appraised with the JBI checklist, and because of substantial heterogeneity, findings were synthesized narratively by population group (SWiM guideline) rather than pooled. Results: Anemia was consistently more prevalent in women than men across all population groups and regions. Female prevalence ranged from about 18–22% in older and community adults to over 65% in female university students, whereas male prevalence ranged from none detected to 28% in a hospital-based sample. The lowest mean hemoglobin (10.4 g/dL) occurred in young women. Between study heterogeneity was considerable (I2 > 99%) and persisted within sex subgroups, so findings were synthesized by population group rather than pooled into a single estimate. Conclusions: Anemia remains a significant public health challenge among women in Saudi Arabia, shaped by an interacting set of dietary, sociocultural, hereditary, and health-system determinants specific to the local context. Beyond confirming the female burden, this review consolidates fragmented national evidence, appraises its quality, and translates the findings into targeted recommendations: dietary counseling to address local inhibitors of iron absorption, screening during peak-risk periods, and integration with existing premarital screening and food-fortification infrastructure.

Association between wealth status and health insurance enrollment among women aged 15–49 years in Tanzania: a secondary analysis of the 2022 Demographic and Health Survey

A relationship between wealth status and health insurance enrollment among women in Tanzania is not well established. This study aimed to fill that gap by determining the association between wealth status and health insurance enrollment among women aged 15–49 years in Tanzania. The study used secondary data from the 2022 Tanzania Demographic and Health Survey (TDHS). The binary dependent variable was health insurance enrollment. Independent variables included women's sociodemographic characteristics. Descriptive and inferential analyses were conducted. The level of association was measured using Adjusted Odds Ratio (AOR) at a 95% confidence interval (CI). A threshold of p  < 0.05 was used to determine statistical significance. Overall, 5.8% (95% CI: 5.1%–6.6%) of women aged 15–49 years in Tanzania were enrolled in health insurance. Logistic regression results indicated that women who belonged to rich households (AOR=2.59; 95% CI: 1.91, 3.53), women aged 35–49 years (AOR=3.86; 95% CI: 2.90, 5.13), women with secondary or higher education (AOR=6.47; 95% CI: 4.17, 10.05), women residing in the Central zone (AOR=1.60; 95% CI: 1.12, 2.28), and women who visited a health facility in the past 12 months (AOR=1.37; 95% CI: 1.14, 1.63) had significantly higher odds of being enrolled. Women who perceived distance to a health facility as not a big problem (AOR=1.70; 95% CI: 1.27, 2.28) and women from female-headed households (AOR=1.29; 95% CI: 1.03, 1.62) also had higher odds of enrollment. Conversely, women who were divorced or separated (AOR=0.50; 95% CI: 0.35, 0.72), women residing in rural areas (AOR=0.68; 95% CI: 0.54, 0.86), and women in the Coastal zone (AOR=0.61; 95% CI: 0.44, 0.86) had significantly lower odds of enrollment. Health insurance enrollment among women of reproductive age in Tanzania is low. There was a positive association between wealth status and health insurance enrollment. The government and other stakeholders should design targeted interventions, including linking households to social protection programs such as the Tanzania Social Action Fund (TASAF), to improve household wealth and thereby increase health insurance enrollment as the country works toward achieving universal health coverage.

High Burden of Iron and Vitamin B12 Deficiency Among Apparently Healthy Indian Infants Aged 9–12 Months: A Secondary Analysis of Cross-Sectional Data