Effect of race and predictors of socioeconomic status on diet quality in the HANDLS Study sample

J Natl Med Assoc. 2010 Oct;102(10):923-30. doi: 10.1016/s0027-9684(15)30711-2.


Purpose: To examine effects of race and predictors of socioeconomic status (SES) on nutrient-based diet quality and their contribution to health disparities in an urban population of low SES.

Design: Data were analyzed from a sample of the Healthy Aging in Neighborhoods of Diversity Across the Life Span (HANDLS) Study participants examining effects of age, sex, race, income, poverty income ratio, education, employment, and smoking status on nutrient-based diet quality as measured by a micronutrient composite index of nutrient adequacy ratios and a mean adequacy ratio. Regression models were used to examine associations and t tests were used to look at racial differences.

Subjects: African American and white adults ages 30 to 64 years residing in 12 predefined census tracts in Baltimore, Maryland.

Results: Sex, age, education, poverty income ratio, and income were statistically significant predictors of diet quality for African Americans, while sex, education, and smoking status were statistically significant for whites. African Americans had lower mean adequacy ratio scores than whites (76.4 vs. 79.1). Whites had significantly higher nutrient adequacy ratios scores for thiamin, riboflavin, folate, B12, vitamins A and E, magnesium, copper, zinc, and calcium, while African Americans had higher vitamin C scores.

Conclusion: Education significantly impacted diet quality in the HANDLS sample, but race cannot be discounted. Whether the racial differences in diet quality are indicative of cultural differences in food preferences, selection, preparation, and availability, or disparities in socioeconomic status remains unclear.

Publication types

  • Research Support, N.I.H., Intramural

MeSH terms

  • Adult
  • Culture
  • Diet*
  • Educational Status
  • Female
  • Health Status Disparities
  • Humans
  • Male
  • Middle Aged
  • Prospective Studies
  • Regression Analysis
  • Socioeconomic Factors