Dose-response association between dietary patterns and gestational diabetes mellitus risk: A systematic review and meta-analysis of observational studies.

Although dietary factors are relevant modifiable risk factors for gestational diabetes mellitus (GDM), the exact association between dietary patterns and GDM remains controversial. Therefore, a systematic review and dose-response meta-analysis of observational studies were conducted to summarize the association between dietary patterns and risk of GDM. PubMed, Scopus, Web of Science, Cochrane Library, and EMbase databases were systematically searched for publications up to March 10, 2020. All observational studies which assessed the risk of GDM according to the categories of healthy or unhealthy dietary patterns derived by either a priori or a posteriori methods were eligible to be included. Pooled effect sizes for the highest vs. lowest categories of healthy/unhealthy dietary patterns were calculated using the random-effects model. Linear and nonlinear dose-response analyses were performed to determine dose-response associations. Thirty-one studies were included, of which 26 studies (80,849 participants) assessed healthy dietary pattern and 15 studies (32,965 participants) assessed the unhealthy dietary pattern. Individuals with a higher adherence to the healthy dietary pattern were less likely to be affected by GDM (RR = 0.86; 95% CI: 0.76-0.96; I 2 = 56.2%). There was a marginally significant association between unhealthy dietary patterns and GDM risk (RR = 1.28; 95% CI: 0.99-1.67; I 2 = 74.7). Significant linear associations were observed between healthy (p = .011) and unhealthy (p = .009) dietary patterns and GDM risk. Pregnant women with a healthier dietary pattern (a diet rich in fruits, vegetables, and whole grains) had lower risk for GDM. In contrast, higher adherence to an unhealthy dietary pattern was associated with increased risk of GDM. Further longitudinal studies are needed to confirm the results.

A 16-year prospective cohort study to evaluate effects of long-term fluctuations in obesity indices of prediabetics on the incidence of future diabetes.

This study aimed to evaluate the patterns of changes in obesity indices over time in prediabetic subjects and to classify these subjects as either having a low, moderate, and high risk for developing diabetes in the future. This study was conducted among 1228 prediabetics. The patterns of changes in obesity indices based on three measurements including first, mean values during the follow-up period, and last visit from these indices were evaluated by using the latent Markov model (LMM). The mean (standard deviation) age of subjects was 44.0 (6.8) years and 73.6% of them were female. LMM identified three latent states of subjects in terms of change in all anthropometric indices: a low, moderate, and high tendency to progress diabetes with the state sizes (29%, 45%, and 26%), respectively. LMM showed that the probability of transitioning from a low to a moderate tendency to progress diabetes was higher than the other transition probabilities. Based on a long-term evaluation of patterns of changes in obesity indices, our results reemphasized the values of all five obesity indices in clinical settings for identifying high-risk prediabetic subjects for developing diabetes in future and the need for more effective obesity prevention strategies.

Patterns of changes in fasting plasma glucose, hemoglobin A1c and the area under the curve during oral glucose tolerance tests in prediabetic subjects: results from a 16-year prospective cohort study among first-degree relatives of type 2 diabetic patients.

AIM: This study aimed to identify the patterns of changes in glycemic indices over time in prediabetics and to classify these subjects as either having a high or low risk for developing diabetes in future. METHODS: This prospective 16-year cohort study was conducted among 1228 prediabetic subjects. Three measurements including first visit, mean values during the follow-up period, and last visit from fasting plasma glucose (FPG), glycosylated hemoglobin (HbA1C), and area under the curve during an oral glucose tolerance test (OGTT AUC) were used to evaluate the patterns of changes by using the latent Markov model (LMM). RESULTS: The mean (standard deviation) age of subjects was 44.0 (6.8) years, and 73.6% of them were female. The LMM identified 2 latent states of subjects in terms of changes in FPG, HbA1c, OGTT AUC, and the combination of these glycemic measures: a low tendency to progress diabetes and a high tendency to progress diabetes with the latent state sizes (87, 13%), (94, 6%), (57, 43%), and (84, 16%), respectively. The LMM showed that the probability of transitioning from a low tendency to a high tendency to progress diabetes was higher than the probability of transitioning in the opposite direction. CONCLUSION: Based on a long-term evaluation of patterns of changes in glycemic indices, we classified prediabetic subjects into 2 groups (high or low risk to progress diabetes states in future). Also, the method used enabled us to estimate the transition probabilities from low- to high-risk states and vice versa. Our results reemphasized the values of all 3 glycemic measures in clinical settings for identifying prediabetic people with a high risk of progressing diabetes and the need for more effective prevention strategies, which should be conducted as urgently in prediabetic life as high-risk subjects.

Patterns of changes in serum lipid profiles in prediabetic subjects: results from a 16-year prospective cohort study among first-degree relatives of type 2 diabetic patients.

BACKGROUND: Lipid abnormality pervasively is associated with the risk of type 2 diabetes mellitus. To the best of our knowledge, there is no study that has examined the longitudinal changes in a wide range of serum lipid profiles in prediabetic subjects in association with the risk of developing type 2 diabetes mellitus in the future. This study aimed to identify the patterns of changes in lipid profiles over time in prediabetic patients and to classify these subjects in order to highlight which patients are at high risk for future diabetes. METHODS: This prospective 16-year (2003-2019) cohort study was conducted among 1228 prediabetic subjects. The study subjects were followed, and the changes in their lipid profiles, including triglycerides, cholesterol, high-density lipoprotein cholesterol, and low-density lipoprotein cholesterol, were evaluated. The latent Markov model was used for data analysis. RESULTS: The mean (standard deviation) age of subjects was 44.0 (6.8) years, and 73.6% of them were female. The latent Markov model identified two latent states of subjects in terms of changes in lipid profiles: a low tendency to progress diabetes / high tendency to progress diabetes (74, 26%). The latent Markov model showed that the transition probability from a "low tendency to progress diabetic" state to a "high tendency to progress diabetic" state was lower than the transition probability from "high tendency to progress diabetic" state to "low tendency to progress diabetic" state. CONCLUSIONS: The present study showed that more than half of the first-degree relatives of T2DM had approximately normal lipid profiles and that these patients are more inclined to transition from a higher- to a lower-tendency diabetic state. These findings confirm the value of regular screening of first-degree relatives of T2DM. Moreover, preventive intervention strategies are recommended to reduce their risk of developing T2DM.

Effect of Herbal Medicine on Vaginal Epithelial Cells: A Systematic Review and Meta-analysis.

OBJECTIVES: The present meta-analysis aimed to assess the effect of the herbal medicine on the vaginal epithelial cells (VECs) among the menopausal subjects. METHODS: The literature related to VECs exposed to various herbal medicines in menopausal women were searched on three databases, MEDLINE (1966-August 2017), Scopus (1990-August 2017) and Cochrane Library (Cochrane Central Register of Controlled Trials; 2014). RESULTS: Totally, the meta-analysis was conducted on 11 randomised controlled trials. Based on the findings, the standardized mean difference (SMD) of maturation value (MV) was observed to be elevated by 0.48% (95% interval confidence [CI], 0.108-0.871; P = 0.012), as well as the heterogeneity was high (I2 = 84%; P < 0.001). The MV revealed a significant increase in soy group (SMD, 0.358; 95% CI, 0.073-0.871; P = 0.014) compared to the control group. CONCLUSIONS: The herbal medicines exhibited a statistically significant effect on the VECs. A significant effect on the VECs was also found in the subgroup analysis of the patients, who received soy. However, further and extensive studies are required to achieve reliable outcomes.