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A Diet Quality Index for Pregnancy detects variation in diet and differences by sociodemographic factors

  • Lisa M Bodnar (a1) (a2) and Anna Maria Siega-Riz (a1) (a2) (a3)

Abstract

Objective:

Methods currently used to assess nutritional status during pregnancy have limitations if one wishes to examine the overall quality of the diet. A Diet Quality Index for Pregnancy (DQI-P) was developed to reflect current nutritional recommendations for pregnancy and national dietary guidelines.

Design:

Dietary intake was assessed during the second trimester using a food-frequency questionnaire. The DQI-P includes eight components: % recommended servings of grains, vegetables and fruits, % recommendations for folate, iron and calcium, % energy from fat, and meal/snack patterning score. Scores can range from 0 to 80; each component contributed 10 points.

Setting:

Two public prenatal clinics in central North Carolina.

Subjects:

N = 2063 pregnant women who participated in the Pregnancy, Infection, and Nutrition (PIN) Study.

Results:

The DQI-P quantitatively differentiated diets. The mean score for the population was 56.0 (standard deviation 12.0). Women who were <30 years old, <350% of poverty, nulliparous and high school graduates had significantly higher overall DQI-P scores. Higher percentages of recommended vegetable servings were consumed by higher-income, older and better-educated women. Greater percentages of recommended intakes of folate and iron were seen among black, low-income and nulliparous women. Higher iron intakes were also seen among women who graduated high school and were less than 30 years old. Other differences were observed for intake of fat and meal/snack pattern. Because this index was based on national recommendations, the DQI-P may be a useful tool for research and public health settings to evaluating overall diet quality of pregnant women.

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Copyright

Corresponding author

*Corresponding author: Email lisa_bodnar@unc.edu

References

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A Diet Quality Index for Pregnancy detects variation in diet and differences by sociodemographic factors

  • Lisa M Bodnar (a1) (a2) and Anna Maria Siega-Riz (a1) (a2) (a3)

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