Quality of diet is associated with insulin resistance in the Cree ( Eeyouch ) indigenous population of northern Québec

• Published in: Nutrition, metabolism, and cardiovascular diseases Vol. 25; no. 1; pp. 85 - 92
• Main Authors: Johnson-Down, L, Labonte, M.E, Martin, I.D, Tsuji, L.J.S, Nieboer, E, Dewailly, E, Egeland, G, Lucas, M
• Format: Journal Article
• Language: English
• Published: Netherlands Elsevier B.V 01.01.2015
• Subjects: Adolescent; Adult; Aged; Arctic Regions - epidemiology; Biomarkers - blood; Cardiovascular; Cross-Sectional Studies; Diabetes; Diabetes Mellitus, Type 2 - epidemiology; Diabetes Mellitus, Type 2 - ethnology; Diabetes Mellitus, Type 2 - etiology; Diabetes Mellitus, Type 2 - metabolism; Diet - adverse effects; Diet - ethnology; Dietary patterns; Female; Health Transition; Humans; Hyperinsulinemia; Indians, North American; Insulin; Insulin Resistance - ethnology; Male; Middle Aged; Nutrition Surveys; Obesity - epidemiology; Obesity - ethnology; Obesity - etiology; Obesity - metabolism; Prevalence; Principal Component Analysis; Quebec - epidemiology; Residence Characteristics; Young Adult; Arctic Regions; Quebec; Hyperinsulinemia; Dietary patterns; Diabetes; Insulin
• ISSN: 0939-4753; 1590-3729
• DOI: 10.1016/j.numecd.2014.08.002

Abstract Background and aims Indigenous people worldwide have a greater disease burden than their non-aboriginal counterparts with health challenges that include increased obesity and higher prevalence of diabetes. We investigate the relationships of dietary patterns with nutritional biomarkers, selected environmental contaminants and measures of insulin resistance in the Cree ( Eeyouch ) of northern Québec Canada. Methods and results The cross-sectional ‘Nituuchischaayihitaau Aschii: A Multi-Community Environment-and-Health Study in Eeyou Istchee’ recruited 835 adult participants (≥18 y) from 7 communities in the James Bay region of northern Québec. The three dietary patterns identified by principal component analysis (PCA) were: inland and coastal patterns with loadings on traditional foods, and a junk food pattern with high-fat and high-sugar foods. We investigated dietary patterns scores (in quantiles) in relation with nutritional biomarkers, environmental contaminants, anthropometry, blood pressure, fasting plasma glucose and insulin, and insulin resistance. Homeostatic model assessment (HOMA-IR) was used as surrogate markers of insulin resistance. ANCOVA ascertained relationships between dietary patterns relationship and outcomes. Greater scores for the traditional patterns were associated with higher levels of n-3 fatty acids, mercury and polychlorinated biphenyls (PCBs) ( P trend <0.001). Higher scores for the junk food pattern were associated with lower levels of PCBs and Vitamin D, but higher fasting plasma insulin and HOMA-IR. Conclusion Our results suggest that poor diet quality accompanied greater insulin resistance. Impacts of diet quality on insulin resistance, as a sign of metabolism perturbation, deserve more attention in this indigenous population with high rates of obesity and diabetes.