Scoring models of a diet quality index and the predictive capability of mortality in a population-based cohort of Swedish men and women

Objective: To examine how different scoring models for a diet quality index influence associations with mortality outcomes. Design: A study within the Malmo Diet and Cancer cohort. Food and nutrient intakes were estimated using a diet history method. The index included six components: SFA, PUFA, fish and shellfish, fibre, fruit and vegetables, and sucrose. Component scores were assigned using predefined (based on dietary recommendations) and population-based cut-offs (based on median or quintile intakes). Multivariate Cox regression was used to model associations between index scores (low, medium, high) and all-cause and cause-specific mortality by sex. Setting: Malmo, the third largest city in Sweden. Subjects: Men (n 6940) and women (n 10 186) aged 44-73 years. During a mean follow-up of 14.2 years, 2450 deaths occurred, 1221 from cancer and 709 from CVD. Results: The predictive capability of the index for mortality outcomes varied with type of scoring model and by sex. Stronger associations were seen among men using predefined cut-offs. In contrast, the quintile-based scoring model showed greater predictability for mortality outcomes among women. The scoring model using median-based cut-offs showed low predictability for mortality among both men and women. Conclusions: The scoring model used for dietary indices may have a significant impact on observed associations with disease outcomes. The rationale for selection of scoring model should be included in studies investigating the association between dietary indices and disease. Adherence to the current dietary recommendations was in the present study associated with decreased risk of all-cause and cause-specific mortality, particularly among men.