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Association between socioeconomic status and diet quality in Mexican men and women: A cross-sectional study.

Nancy López-OlmedoBarry M PopkinLindsey Smith Taillie
Published in: PloS one (2019)
Examining the potential differences in diet quality among socioeconomic status (SES) subgroups in Mexican adults may help to explain SES disparities in the burden of non-communicable diseases. We determined the association between SES, gender and diet quality among Mexican adults. We analyzed data from adults participating in the subsample with dietary information from the Mexican National Health and Nutrition Survey 2012 (n = 2,400), and developed the Mexican Diet Quality Index based on the Mexican Dietary Guidelines. We tested the interaction between sex and SES indicators using multivariable linear regression models. Sex was not a modifier; therefore, the analyses were carried out in the overall sample of men and women. The mean age was 42 (SE = 0.4) years, the total diet quality score was 38 (SE = 0.4), and a high percentage of men and women were classified with reading/writing skills or 3-9 years of school. A higher percentage of adults were classified with high versus medium or low assets index. In the multivariable model further adjusted for the assets index, for adults with education in the reading and/or 3-9 years of schooling and those with ≥10 years of school, there was a 3.7 and 5.8 points lower total diet quality score than with adults with no reading/writing skills (p < 0.05). Likewise, in multivariable model further adjusted for educational level, the total diet quality score was 2.5 points and 3.3 points lower in adults classified with medium and high assets index, respectively, versus low assets index (p < 0.05). The difference between individuals with medium and high assets index was not statistically significant. Although there is currently better diet quality among adults with low SES, this needs to continue to be monitored as Mexico progress through the nutrition transition.
Keyphrases
  • physical activity
  • weight loss
  • quality improvement
  • healthcare
  • mental health
  • risk factors
  • working memory
  • risk assessment
  • electronic health record
  • deep learning