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Adherence to the 2015 Dietary Guidelines for Americans (DGA) and Risk of Healthy and Unhealthy Obesity among Canadian Adults.
Author(s) -
Jessri Mahsa,
Lou Wendy,
L'Abbe Mary
Publication year - 2016
Publication title -
the faseb journal
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.709
H-Index - 277
eISSN - 1530-6860
pISSN - 0892-6638
DOI - 10.1096/fasebj.30.1_supplement.131.3
Subject(s) - medicine , quartile , national health and nutrition examination survey , obesity , odds ratio , multinomial logistic regression , epidemiology , odds , logistic regression , population , disease , demography , environmental health , gerontology , confidence interval , machine learning , sociology , computer science
Recently, the scientific community has recognized the importance of differentiating between obesity phenotypes; however, less attention has been given to this issue in nutritional epidemiology. The objective of this study was to examine whether closer adherence to the recommendations proposed in the Scientific Report of the 2015 Dietary Guidelines for Americans (DGA), as measured by an updated 2015 DGA Adherence Index (DGAI), is differentially associated with risk of obesity with and without an accompanying chronic disease, including diabetes, hypertension and heart disease (i.e., healthy and unhealthy obesity). Weighted multinomial logistic regression‐GLM was used to examine the associations between the a priori 19‐score DGAI and healthy and unhealthy obesity among 11,748 participants aged≥18 years in the Canadian Community Health Survey 2.2. All models were additionally adjusted for the energy misreporting status to account for this systematic bias. The mean 2015 DGAI score was 8.82 (±0.051)(Possible Max:19) and its two subscores (“food intake” and “healthy choice”) were 3.92(±0.038) (Possible Max:11) and 4.90 (±0.028) (Possible Max:8), respectively, which indicates that our population was adherent to less than 50% of recommendations. After adjusting for age, sex and energy misreporting, adherence to the 2015 DGA recommendations decreased the odds of being unhealthy obese monotonically from Odds Ratio (OR): 2.413 (1.732–3.361) in quartile 1 (poorest diet), to 2.088 (1.505–2.898) in quartile 2, and 1.412 (1.01–1.973) in the third quartile of the 2015 DGAI score, compared to the fourth quartile category (healthiest diet) (p‐trend<0.0001). The odds of being obese without a chronic disease (healthy obese) also decreased from 2.29 (1.482–3.539) in quartile 1, to 2.328 (1.485–3.649) in quartile 2, and 1.629 (0.932–2.849) in the third quartile category of the 2015 DGAI, as compared to the fourth quartile (p‐trend<0.0001). In the same model, individuals in the first quartile of the 2015 DGAI (poorest diets) showed 1.424 (1.031–1.966) times higher risk of being lean with at least one accompanying chronic disease, compared to those in the fourth quartile (healthiest diet). Our findings suggest that individuals with the obesity phenotype coupled with an accompanying metabolic disorder may benefit the most from following the 2015 DGA, even though unhealthy lean and healthy obese phenotypes are also reduced markedly as a result of closer compliance to the 2015 DGA, albeit not as strongly as unhealthy obesity phenotype. Therefore, differentiating unhealthy obesity from healthy obesity has important implications for public health and clinical management of obesity. Even though none of the participants met all the 2015 DGA recommendations, our results support the value of compliance to the 2015 DGA for reducing the cumulative prevalence of chronic diseases at the population level. Owing to the similarity of the North American dietary recommendations, these findings suggest that the 2015 DGA may be adapted to improve dietary behaviours in the Canadian context. Support or Funding Information This research was supported by funds to the Canadian Research Data Centre Network from the Social Science and Humanities Research Council, the Canadian Institute for Health Research (CIHR), the Canadian Foundation for Innovation and Statistics Canada. M. J. is supported by the Canadian Institute of Health Research (CIHR) Vanier Canada Graduate Scholarship, the CIHR/Cancer Care Ontario (CCO) Population Intervention for Chronic Disease Prevention (PICDP): a Pan‐Canadian Fellowship, and the Ontario Graduate Scholarship (OGS). M. L. is the Earle W. McHenry professor and is supported by the chair‐endowed unrestricted research funds, University of Toronto.