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Despite the institution of mandatory folic acid fortification in the US, folate deficiencies still occur and are associated with an increased risk of several conditions. Since little is known regarding the relationship between folate status and other clinical, demographic, and healthcare-related characteristics, the objective of the study was to compare healthcare-related characteristics among US child-bearing age women with low vs normal red blood cell (RBC) folate levels. Data from the 2003-2006 National Health and Nutrition Examination Survey (NHANES) were used to conduct a retrospective cohort study. Women (aged 18-45 when surveyed) were categorized in two cohorts for comparison: normal RBC folate level (≥ 140 ng/ml, NFL) and low RBC folate level (<140 ng/ml, LFL). Of the 2816 subjects, 5.9% were assigned to the LFL cohort and were significantly younger (28 vs 30 years, p=0.01); a greater proportion were 18-25 years old (55.7% vs 39.9%, p<0.001) or African-American (55.1% vs 22.3%, p<0.01). A lower proportion of LFL women were insured (67.3% vs 75.5%, p=0.01) with low rates of private insurance (39.5% vs 53.1%, p<0.01), while Medicaid/SCHIP coverage was similar (16.8% vs 15.1%, p=0.56). Predictors of low folate levels included aged 36-45 years (OR: 2.14 [95% CI: 1.04, 4.39]) and never being married (2.65 [1.34, 5.24]), while a household income ≥ $75,000 reduced the likelihood of having low folate levels (0.20 [0.06, 0.73]). The proportion of women with low folate levels was small, with the sample size limiting the ability to adjust for other factors during analysis. Medical histories were based on patient interviews and are subject to recall bias. LFL women are younger and have low rates of private insurance coverage compared to women with normal folate levels. Differences in age, marital status, and household income are associated with folate status.

Citation

Vijay N Joish, Grace Lin, Richard Lynen. Healthcare-related characteristics of low vs normal folate levels among women of child-bearing age. Journal of medical economics. 2012;15(5):807-16

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PMID: 22458715

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