Diet quality and therapeutic targets in patients with type 2 diabetes: evaluation of concordance between dietary indexes

Low diet quality is associated with adverse levels of metabolic health markers and clustering of risk factors in adults with type 2 diabetes

BACKGROUND

Nutritional recommendations for diabetes management emphasise an overall, healthful diet consistent with the guidelines for the general population. The present study assessed the relationship of diet quality, as measured by Healthy Eating Index-2015 (HEI-2015), with metabolic health markers and risk factor clustering in type 2 diabetes patients using National Health and Nutrition Examination Survey 2011-2016 data.

METHODS

HEI-2015 diet quality scores were calculated using 24-h dietary recalls. Adults with type 2 diabetes (n = 2220) were assessed for: (1) hyperglycaemia; (2) overweight/obesity; (3) dyslipidaemia; and (4) hypertension. Logistic regression examined associations of diet quality quartiles with odds of hyperglycaemia, overweight/obesity, dyslipidaemia and hypertension, as well as odds of clustering of these risk factors.

RESULTS

Odds of overweight/obesity and hyperglycaemia were significantly greater for participants in the lowest HEI-2015 quartile compared to those in the highest quartile. Furthermore, individuals in the bottom two HEI-2015 quartiles had increased odds of dyslipidaemia. Those in the lowest quartile also had significantly higher odds of having ≥ 2, ≥ 3 and 4 risk factors (vs. having ≤ 1 risk factor).

CONCLUSIONS

Low diet quality was related to increased odds of hyperglycaemia, dyslipidaemia, overweight/obesity and risk factor clustering. Findings imply poorer prognosis of diabetes in individuals with low diet quality.

Food purchases in households with and without diabetes based on consumer purchase data

OBJECTIVES

Dietary recommendations for individuals with diabetes are easy to provide, but adherence is difficult to monitor. The objective of this study was to investigate whether there was a difference in grocery purchases between households with and without diabetes.

STUDY DESIGN

Cohort study.

METHODS

Consumer purchase data in 2019 was collected from 6662 households donating their supermarket receipts via a receipt collecting service. Of these households, 718 included at least one individual with diabetes. The monetary percentages spent on specific food groups were used to characterize households using all purchases in 2019. A probability index model was used to compare households with diabetes to households without diabetes.

RESULTS

We included 405,264 shopping trips in 2019 attributed to 6662 households. Both households with and without diabetes spent the highest monetary percentage on sweets (with diabetes: 9.3%, without diabetes: 8.8%), with no statistically significant difference detected. However, compared to households without diabetes, households with diabetes had a significantly higher probability of spending a higher monetary percentage on butter, oil and dressings; non-sugary drinks; processed red meat and ready meals as well as a significantly lower probability of spending a higher monetary percentage on accessory compounds; alcoholic beverages; eggs; grains; rice and pasta, and raw vegetables.

CONCLUSIONS

Households with diabetes spent a relatively higher monetary value on several unhealthy foods and less on several healthy groceries compared to households without diabetes. There is a need for more diabetes self-management education focused on including more healthy dietary choices in their household grocery purchases.

Absolute and Relative Agreement between the Current and Modified Brazilian Cardioprotective Nutritional Program Dietary Index (BALANCE DI) and the American Heart Association Healthy Diet Score (AHA-DS) in Post Myocardial Infarction Patients

The American Heart Association Diet Score (AHA-DS) defines the cardiovascular health, and the Brazilian Cardioprotective Nutritional Program Dietary Index (BALANCE DI) was designed to evaluate diet quality in secondary cardiovascular prevention settings. Our aim was to assess the absolute and relative agreement between both tools in Brazilian adults after a myocardial infarction (MI). In this cross-sectional study, 473 individuals were included and had their diet assessed by a 24 h food recall and a semi-quantitative Food Frequency Questionnaire. The weighted Kappa between BALANCE DI and primary AHA-DS was 0.66 (95% CI: 0.08-0.21), and between BALANCE DI and total AHA-DS was 0.70 (95% CI: 0.20-0.32). To improve the agreement between the tools, modifications were made to the BALANCE DI scoring system. The weighted Kappa between New BALANCE DI and primary AHA-DS was 0.77 (95% CI: 0.36-0.48), and between BALANCE DI and total AHA-DS was 0.76 (95% CI: 0.34-0.46). The mean bias observed between the New BALANCE DI as compared to the primary and total AHA-DS was -16% (-51 to 19) and -8% (-41 to 24), respectively. Our results suggest that the New BALANCE DI may be a useful tool to evaluate diet quality in post MI patients.