Dietary habits, oral impact on daily performance and type 2 diabetes: a matched case-control study from Sudan

Abstract Background It is evident that social and behavioural factors influence on individuals’ general health and quality of life. Nevertheless, information about the influence of dietary habits on oral health-related quality of life is limited; especially among patients with type 2 diabetes (T2D). The aim of this study was to examine the influence of dietary habits and clinical oral health indicators on oral health-related quality of life in individuals with and without T2D. Methods A total of 149 T2D cases and 298 controls were recruited for this age and gender matched case-control study. Questionnaire-guided interviews were conducted to collect data about socio-demographic characteristics, consumption of food items per week (milk, meat, eggs, vegetables, fruits, sweets and bread) and oral impact on daily performance (OIDP). Plaque index, bleeding on probing, probing depth, tooth mobility, decayed, missing and filled teeth index (DMFT) and root caries were recorded. Results Difficulty with eating and sleeping were more frequently reported by T2D cases (23.5% and 16.1%, respectively) than by the controls (10.7% and 5.0%, respectively) (P  0). The corresponding ORs were 1.23 (1.01–4.89) and 2.10 (1.08–4.09), respectively. Participants with low consumption of meat and vegetables were more likely than their counterparts with high consumption to report any oral impact. The corresponding ORs were 0.46 (0.25–0.83) and 0.38 (0.17–0.87), respectively. There was a significant interaction between diabetic status and meat consumption as well as between diabetic status and bread consumption. Conclusions Oral impacts were more frequently reported in T2D cases than controls. Independent of diabetic- and oral clinical status, dietary habits discriminated between individuals with and without oral impacts. The influence of meat and bread consumption on OIDP varied significantly according to T2D status

Clinical and self-reported oral health indicators by subgroups of T2DM cases according to glycemic control and duration of diabetes.

*<p><i>P</i><0.05.</p>**<p><i>P</i><0.01.</p

Correlations between number of sites with PD ≥ 4mm and the amounts of the detected biomarkers.

<p>^<b>a</b> Spearman’s correlation.</p><p><b>GIP</b>: gastric inhibitory polypeptide, <b>GLP-1</b>: glucagon-like peptide-1, <b>PAI-1</b>: plasminogen activator inhibitor-1.</p><p>Correlations between number of sites with PD ≥ 4mm and the amounts of the detected biomarkers.</p

Distribution of confounders and main explanatory variables according to T2DM status (n = 457).

*<p><i>P</i><0.05.</p>**<p><i>P</i><0.01.</p

All main explanatory variables according to T2DM status adjusted for possible confounding variables, (n = 447).

*<p><i>P</i><0.05.</p>**<p><i>P</i><0.01.</p><p>a) Adjusted for employment status, educational level, consumption of sugary drinks, hypertension, smoking, plaque index and regular dental attendance.</p><p>b) Adjusted for employment status, educational level, consumption of sugary drinks, hypertension, smoking, plaque index, regular dental attendance and other main explanatory variables.</p

Logistic regression analysis with periodontal status as dependent variable (yes/no).

<p>^<b>a</b> Adjusted for age, gender, plaque index and total GCF protein.</p><p><b>OR</b>: adjusted odds ratio, <b>CI</b>: confidence interval, <b>SE</b>: standard error, <b>GIP</b>: gastric inhibitory polypeptide, <b>GLP-1</b>: glucagon-like peptide-1, <b>PAI-1</b>: plasminogen activator inhibitor-1.</p><p>Logistic regression analysis with periodontal status as dependent variable (yes/no).</p

DMFT regressed on duration of T2DM; adjusted for age, gender and regular dental attendance.

*<p><i>P</i><0.05.</p>**<p><i>P</i><0.01.</p><p>-2 Log likelihood  =  183.536, Cox & Snell R² = 0.114, Nagelkerke R² = 0.155.</p

Mobility index regressed on the level of glycemic control; adjusted for age and gender.

*<p><i>P</i><0.05.</p>**<p><i>P</i><0.01.</p><p>-2 Log likelihood  =  191.545, Cox & Snell R² = 0.093, Nagelkerke R² = 0.124.</p

Influence of type 2 diabetes on local production of inflammatory molecules in adults with and without chronic periodontitis: A cross-sectional study

Background Pathological changes in periodontal tissues are mediated by the interaction between microorganisms and the host immune-inflammatory response. Hyperglycemia may interfere with this process. The aim of this study was to compare the levels of 27 inflammatory molecules in the gingival crevicular fluid (GCF) of patients with type 2 diabetes, with and without chronic periodontitis, and of chronic periodontitis subjects without diabetes. A putative correlation between glycated haemoglobin (HbA1c) and levels of the inflammatory molecules was also investigated. Methods The study population comprised a total of 108 individuals, stratified into: 54 with type 2 diabetes and chronic periodontitis (DM + CP), 30 with chronic periodontitis (CP) and 24 with type 2 diabetes (DM). Participants were interviewed with the aid of structured questionnaire. Periodontal parameters (dental plaque, bleeding on probing and periodontal pocket depth) were recorded. The GCF levels of the 27 inflammatory molecules were measured using multiplex micro-bead immunoassay. A glycated haemoglobin (HbA1c) test was performed for patients with diabetes by boronate affinity chromatography. Results After adjustment for potential confounders, the DM + CP group had higher levels of IL-8 and MIP-1β, and lower levels of TNF-α, IL-4, INF-γ, RANTES and IL-7 compared to the CP group. Moreover, the DM + CP group had lower levels of IL-6, IL-7 and G-CSF compared to the DM group. The DM group had higher levels of IL-10, VEGF, and G-CSF compared to the CP group. The levels of MIP-1α and FGF were lower in diabetes patients (regardless of their periodontal status) than in chronic periodontitis subjects without diabetes. Diabetes patients (DM + CP and DM) had higher Th-2/Th-1 ratio compared to the CP group. HbA1c correlated positively with the pro-inflammatory cytokines (Pearson correlation coefficient = 0.27, P value: 0.02). Conclusion Type 2 diabetes and chronic periodontitis may influence the GCF levels of inflammatory molecules synergistically as well as independently. Type 2 diabetes was associated with high Th-2/Th-1 ratio, and modulated the local expression of molecules involved in the anti-inflammatory and healing processes