Systems Epidemiology: A New Direction in Nutrition and Chronic Disease Research

(1) Background: Both tooth loss and diabetes have high global prevalence, and both have a significant influence on patients’ general health and quality of life. Previous research has indicated a possible connection between tooth loss and diabetes, but it has been unclear whether tooth loss has an effect on the development of diabetes and how it affects it. We aim to investigate the relationship between insulin resistance (IR) and tooth loss and examine how the systemic immune-inflammation index (SII) level and diet quality mediate it. (2) Methods: The cross-sectional study data were obtained from the National Health and Nutrition Examination Survey (NHANES). After describing and comparing baseline data, we used regression models to evaluate the relationship between IR and tooth loss, diet quality and tooth loss and IR, SII and tooth loss and IR. Furthermore, we applied bootstrapping to test the mediation effect of diet quality and SII between tooth loss and IR. Diet quality is reflected by the HEI (Healthy Eating Index)-2015 score. (3) Results: The total number of subjects included was 8197, with 3861 individuals belonging to the IR group (HOMA-IR ≥ 2.5) and 4336 in the non-IR group (HOMA-IR < 2.5). In the model with all covariates adjusted, tooth loss in the fourth quartile was found to be positively correlated with an increase in HOMA-IR (OR = 1.301; 95% confidence interval (CI) = [1.102, 1.537]; p < 0.001) compared to the first quartile; tooth loss in the fourth quartile correlated with the HEI-2015 score compared to the first quantile (β = −0.121, 95% CI = [−4.839, −2.974], p < 0.001); and the highest number of tooth loss was found to have a significant effect on SII (β = 0.032; 95%CI = [1.777, 47.448]; p < 0.05). Compared to average diet quality, best diet quality acts as a safeguard against elevated HOMA-IR (OR = 0.776; 95% CI = [0.641, 0.939]; p < 0.01); inadequate diet quality is a risk factor (OR = 1.267; 95%CI = [1.138, 1.411]; p < 0.001) conversely. Meanwhile, it can be seen that compared with the first quantile of SII, the highest score is significantly correlated with the higher incidence of IR (OR = 1.363; 95%CI = [1.179, 1.575]; p < 0.001). Diet quality and SII played a partial mediating role in the relationship between HOMA-IR and tooth loss, and the mediating effect ratio for the total effect value was 4.731% and 4.576%, respectively. The mediating effect of SII and diet quality in the association of the relationship between HOMA-IR and tooth loss both was 0.003 (95%CI = [0.001, 0.004]). (4) Conclusions: Our study revealed the relationship between IR and tooth loss, and further explored the mediating role of SII and diet quality between the number of missing teeth and IR, emphasizing that improving diet quality and reducing SII can effectively prevent and treat IR and related diseases. It provides new theoretical support for the study of IR mechanisms and new ideas and approaches to deal with related diseases. Full article

The study aimed to assess the associations of dietary patterns and circadian syndrome (CircS). Data from National Health and Nutrition Examination Survey (NHANES) 2005–2016 were analyzed (n = 10,486). Factor analysis was used to construct dietary patterns based on two 24 h food recalls. CircS was defined based on components of the metabolic syndrome, with the addition of short sleep and depression symptoms. Multivariable logistic regression was used to analyze the associations. Two major dietary patterns were identified. The Western dietary pattern had high loadings of refined grains, solid fats, added sugars, and red and cured meats, while the prudent pattern was characterized by a high intake of vegetables, whole grains, oils, nuts, and seeds. The prevalence of CircS was 41.3%. Comparing extreme quartiles of intake, the odds ratios (OR) for having CircS were 1.96 (95%CI 1.53–2.53) and 0.71 (95%CI 0.58–0.86) for the Western pattern and prudent pattern, respectively. The association between the Western dietary pattern and CircS was stronger among men (OR = 2.05; 95%CI 1.48–2.85) and those with low income (OR = 1.94; 95%CI 1.27–2.96) and high education (OR = 3.38; 95%CI 1.90–6.04). The Western dietary pattern was associated with a higher likelihood of having CircS, while the prudent pattern was inversely associated with CircS. Full article

(1) Background: We investigated the effects of a 12-week exercise intervention with or without vitamin D supplementation on insulin resistance and the plasma lipidome of participants with type 2 diabetes. We further explored whether the effects of the intervention on glycemic parameters could be associated with the baseline lipidome. (2) Methods: Sixty-one participants were randomly allocated to control (Con), exercise (EX), vitamin D (VD), and EX + VD groups. Multiple glycemic and anthropometric parameters were evaluated before and after intervention. The homeostasis model assessment of insulin resistance (HOMA-IR) was the primary outcome. The plasma lipidome was analyzed before, after, and at an additional 12-week follow-up. Machine learning was applied to establish prediction models for responsiveness of glycemic control. (3) Results: Our interventions failed to improve the HOMA-IR index while fasting glucose was reduced in the EX + VD group (change%, −11.9%; effect size, 0.65; p < 0.05). Both EX and VD interventions altered the plasma lipidome, with EX + VD intervention considerably affecting levels of lyso-phosphatidylcholines and triglycerols containing long-chain unsaturated fatty acids. Such effects could last until 12 weeks after intervention. Notably, there was high inter-individual variability in glycemic parameters including HOMA-IR in response to the interventions, which could be predicted with great accuracy using an optimal panel of baseline lipid predictors alone or in combination with clinical indices, as assessed by an area under the receiver operating characteristic curve value of over 0.9. (4) Conclusions: Although substantial alterations were observed in the plasma lipidome related to glycemic control, our intervention failed to improve HOMA-IR scores, which may have been predominately due to the large inter-individual variability in responses. Basal plasma lipid levels could potentially predict an individual’s response to intervention, highlighting the necessity of personalized nutrition. Full article