Development of a Healthy Eating Index for patients with type 2 diabetes

Dietary Quality Analysis Methods for the Type 2 Diabetes Mellitus Population: A Scoping Review

BACKGROUND

High diet quality is associated with improved glycemic control in type 2 diabetes mellitus (T2DM) patients. Thus, mapping the dietary analysis methods that lead to the assessment of diet quality is essential for promoting glycemic control in individuals with T2DM. Therefore, this scoping review aimed to map and synthesize the available evidence on the use of dietary analysis methods to assess diet quality in individuals with T2DM.

METHODS

This review was conducted following the Manual for Evidence Synthesis proposed by the Joanna Briggs Institute and the Preferred Reporting Items for Systematic Reviews and Meta-Analyses Extension for Scoping Reviews Checklist. Articles were searched in the MEDLINE (via PubMed), CINAHL (EBSCO), Embase, LILACS/BVS, Bireme, Scopus, and Web of Science databases. Additionally, grey literature was searched using Google Scholar. The protocol was registered in the Open Science Framework (DOI 10.17605/OSF.IO/HSKU9). Studies that utilized dietary analysis methods to assess diet quality in individuals with T2DM were included.

RESULTS

Overall, 3761 studies were identified, and after the selection process, 33 publications were included for full analysis. Twenty-five indices were mapped to assess diet quality in individuals with T2DM. Only the Diabetes Healthy Eating Index was specific to this population. Considering the application of these methods, most indices were linked to the lowest scores, indicating lower diet quality, poor glycemic control, and other unfavourable health outcomes for the participants.

CONCLUSION

Despite the existence of various dietary methods for analysing diet quality, only one index was specific to individuals with T2DM. It is important to assess the applicability of these methods, considering that the quantity consumed must be evaluated to promote better glycemic control in this population.

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.

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

Background

This study aimed to evaluate the concordance between two dietary indexes, the Healthy Eating Index (HEI) and the Diabetes Healthy Eating Index (DHEI), in evaluating diet quality and its possible association with therapeutic targets in patients with type 2 diabetes.

Methods

Cross-sectional study of outpatients with type 2 diabetes mellitus treated at a university hospital. Dietary information was obtained from a quantitative food frequency questionnaire (previously validated for use in patients with type 2 diabetes) and converted into daily intakes. Diet quality was assessed using two dietary indexes: HEI (12 components, nine food groups and three moderation components) and DHEI (10 components, six food groups, three nutrient groups, and one for variety of diet). In both indexes, the sum of the scores for each component yields an overall score converted on a scale from 0 to 100%; diet quality is subsequently ranked as low (<51%), needing improvement (51–80%), or high (>80%). Patients underwent clinical and laboratory assessment. Those with fasting blood glucose values 70–130 mg/dL, A1c < 7%, total cholesterol <200 mg/dL, LDL-cholesterol <100 mg/dL, and triglycerides <150 mg/dL were considered to meet therapeutic targets. All analyses were conducted in PASW Statistics 18.0, and p < 0.05 deemed significant.

Results

We analyzed 148 patients with type 2 diabetes (73% white, mean age 63.2 ± 9.4 years, median diabetes duration 10 [IQR 5–19] years, mean A1c% 8.4 ± 2.0%, and mean BMI 30.5 ± 4.2 kg/m²). Mean energy intake was 2114 ± 649 kcal/day. DHEI scores were 17.0 (95%CI -6.8 to 41.0) points lower than HEI scores (55.9 ± 14.2% vs. 72.9 ± 10.7%, respectively; P < 0.001), suggesting there is no agreement (Bland-Altman method), and the Pearson correlation coefficient was 0.55 (P < 0.001). More patients were classified as having a low-quality diet by the DHEI than by the HEI (38.5% vs. 1.4%; P < 0.001). A higher proportion of patients (35.7%) with out-of-target total cholesterol levels had a low-quality diet evaluated by the DHEI (P = 0.03). We did not find associations between overall score of HEI and therapeutic targets.

Conclusions

In its intended population of patients with type 2 diabetes, the DHEI seems to be a more rigorous tool to evaluate association between diet quality and changes in metabolic parameters.

Electronic supplementary material

The online version of this article (10.1186/s12937-017-0296-8) contains supplementary material, which is available to authorized users.