Short Body Height and Pre-pregnancy Overweight for Increased Risk of Gestational Diabetes Mellitus: A Population-Based Cohort Study

Advanced Mass Spectrometry-Based Biomarker Identification for Metabolomics of Diabetes Mellitus and Its Complications

Over the years, there has been notable progress in understanding the pathogenesis and treatment modalities of diabetes and its complications, including the application of metabolomics in the study of diabetes, capturing attention from researchers worldwide. Advanced mass spectrometry, including gas chromatography-tandem mass spectrometry (GC-MS/MS), liquid chromatography-tandem mass spectrometry (LC-MS/MS), and ultra-performance liquid chromatography coupled to electrospray ionization quadrupole time-of-flight mass spectrometry (UPLC-ESI-Q-TOF-MS), etc., has significantly broadened the spectrum of detectable metabolites, even at lower concentrations. Advanced mass spectrometry has emerged as a powerful tool in diabetes research, particularly in the context of metabolomics. By leveraging the precision and sensitivity of advanced mass spectrometry techniques, researchers have unlocked a wealth of information within the metabolome. This technology has enabled the identification and quantification of potential biomarkers associated with diabetes and its complications, providing new ideas and methods for clinical diagnostics and metabolic studies. Moreover, it offers a less invasive, or even non-invasive, means of tracking disease progression, evaluating treatment efficacy, and understanding the underlying metabolic alterations in diabetes. This paper summarizes advanced mass spectrometry for the application of metabolomics in diabetes mellitus, gestational diabetes mellitus, diabetic peripheral neuropathy, diabetic retinopathy, diabetic nephropathy, diabetic encephalopathy, diabetic cardiomyopathy, and diabetic foot ulcers and organizes some of the potential biomarkers of the different complications with the aim of providing ideas and methods for subsequent in-depth metabolic research and searching for new ways of treating the disease.

Dietary diversity and associated factors among women attending antenatal clinics in the coast region of Tanzania

BACKGROUND

Antenatal care (ANC) is crucial for reducing maternal morbidity and mortality, especially in low-resource settings. During antenatal care, women are provided with resources for enhancing their dietary diversity, like nutrition education and counseling. Improved nutrition knowledge influences positive nutritional behavior change, like women's improved dietary diversity, which may increase the likelihood of a healthier pregnancy and delivery experience.

OBJECTIVE

This study aim was to assess dietary diversity and associated factors among pregnant women attending antenatal care in the Coast region of Tanzania.

METHODS

The descriptive cross-sectional study design was used to assess dietary diversity and associated factors among 338 pregnant women. A semi-structured questionnaire collected information from pregnant women on social demographic characteristics, nutrition knowledge and dietary diversity. Women were classified as having a varied diet if they had consumed at least five of the ten food groups over the previous twenty-four hours. Multivariable logistic regression analyses were used to identify predictors of dietary diversity in pregnant women.

RESULTS

Only 28% (95% CI: 23.5-33.1) (n = 95) of pregnant women met the minimum dietary diversity, and 18% (95% CI: 13.8-21.9) (n = 59) were considered to have a high level of nutrition knowledge. Living near a health facility (AOR = 1.77, CI 1.02, 3.06), having high nutrition knowledge (AOR = 2.58, 95% CI: 1.36, 4.89), and being pregnant for the first time (AOR = 2.44, 95% CI: 1.09, 5.44) were associated with adequate dietary diversity.

CONCLUSION

Pregnant women in the study were found to have low knowledge about nutrition and inadequate dietary diversity intake. The findings underscore the need to improve nutrition knowledge provision in antenatal clinics by emphasizing the importance of a diversified and high-quality diet. Healthcare providers in antenatal care clinics should consistently provide nutrition education and counseling to pregnant women and promote their diversified food consumption. Such knowledge may eventually promote healthier pregnancy and child development by curbing the nutritional deficiencies experienced during pregnancy.

Early pregnancy body mass index and gestational weight gain: A mediating or moderating factor for short stature and risk of gestational diabetes mellitus?

This study examined the association between height and the risk of Gestational Diabetes Mellitus (GDM), and whether this association was mediated or moderated by early pregnancy body mass index (BMI) and gestational weight gain (GWG) that are known independent risk factors for GDM. Data of a retrospective cohort of pregnant women (N = 1,945) were extracted from antenatal clinic cards. The cut-off values of height in relation to risk of GDM were identified using receiver operating characteristic analysis and four categories of height were derived: < 150 cm, 150–155 cm, 156–160 cm, and > 160cm. Mediation analysis was performed using the Preacher and Hayes bootstrapping method while the moderation effect was tested with multiple regression analysis with interaction terms. Although there was no mediation effect of BMI and GWG on the association between height and risk of GDM, both factors moderated this association with a significant association between shorter height and risk of GDM was observed in overweight / obese women (height < 150 cm: AOR = 1.41, 95% CI = 1.03–2.44; height 156–160 cm: AOR = 1.48, 95% CI = 1.03–2.14). Overweight / obese women with height < 150 cm and excessive GWG at the end of the second trimester (AOR = 2.25, 95% CI = 1.45–4.17) had significantly higher risk of GDM than those without these factors. Short stature (< 150 cm) was significantly associated with GDM risk among OW/OB women with excessive gestational weight gain at the end of second trimester. This finding underscores the importance of maintaining a healthy BMI during reproductive age and gaining weight in recommended range during pregnancy.

Gender Differences Between the Phenotype of Short Stature and the Risk of Diabetes Mellitus in Chinese Adults: A Population-Based Cohort Study

OBJECTIVE

Previous studies have shown that there are significant regional and gender differences in the association between the phenotype of short stature and diabetes mellitus (DM). The purpose of this study was to investigate the gender difference between the phenotype of short stature and the risk of DM in the Chinese population.

METHODS

The sample included 116,661 adults from 32 locations of 11 cities in China, of which the average height of men and women was 171.65 and 160.06 cm, respectively. Investigators retrospectively reviewed annual physical examination results for follow-up observations and set confirmed DM events as the outcome of interest. Multivariate Cox regression, restricted cubic spline, and piecewise regression models were used to check the association between height and DM risk.

RESULTS

During an average observation period of 3.1 years, there were 2,681 of 116,661 participants who developed new-onset DM, with a male to female ratio of 2.4 to 1. After full adjustment for confounders, we confirmed that there was a significant negative correlation between height and DM risk in Chinese women (HR per 10 cm increase: 0.85, 95% CI: 0.74-0.98), but not in men (HR per 10 cm increase: 1.16, 95% CI: 0.98-1.14). Additionally, through restricted cubic spline and piecewise regression analysis, we determined that the height of 157-158 cm may be the critical point for short stature used to assess the risk of DM in Chinese women.

CONCLUSIONS

In the Chinese population, female short stature phenotype is related to increased DM risk, among which 157-158 cm may be the saturation effect point of female short stature for predicting DM risk.

Current progress in metabolomics of gestational diabetes mellitus

Gestational diabetes mellitus (GDM) is one of the most common metabolic disorders of pregnancy and can cause short- and long-term adverse effects in both pregnant women and their offspring. However, the etiology and pathogenesis of GDM are still unclear. As a metabolic disease, GDM is well suited to metabolomics study, which can monitor the changes in small molecular metabolites induced by maternal stimuli or perturbations in real time. The application of metabolomics in GDM can be used to discover diagnostic biomarkers, evaluate the prognosis of the disease, guide the application of diet or drugs, evaluate the curative effect, and explore the mechanism. This review provides comprehensive documentation of metabolomics research methods and techniques as well as the current progress in GDM research. We anticipate that the review will contribute to identifying gaps in the current knowledge or metabolomics technology, provide evidence-based information, and inform future research directions in GDM.

Development and validation of an early pregnancy risk score for the prediction of gestational diabetes mellitus in Chinese pregnant women

OBJECTIVE

To develop and validate a set of risk scores for the prediction of gestational diabetes mellitus (GDM) before the 15th gestational week using an established population-based prospective cohort.

METHODS

From October 2010 to August 2012, 19 331 eligible pregnant women were registered in the three-tiered antenatal care network in Tianjin, China, to receive their antenatal care and a two-step GDM screening. The whole dataset was randomly divided into a training dataset (for development of the risk score) and a test dataset (for validation of performance of the risk score). Logistic regression was performed to obtain coefficients of selected predictors for GDM in the training dataset. Calibration was estimated using Hosmer-Lemeshow test, while discrimination was checked using area under the receiver operating characteristic curve (AUC) in the test dataset.

RESULTS

In the training dataset (total=12 887, GDM=979 or 7.6%), two risk scores were developed, one only including predictors collected at the first antenatal care visit for early prediction of GDM, like maternal age, body mass index, height, family history of diabetes, systolic blood pressure, and alanine aminotransferase; and the other also including predictors collected during pregnancy, that is, at the time of GDM screening, like physical activity, sitting time at home, passive smoking, and weight gain, for maximum performance. In the test dataset (total=6444, GDM=506 or 7.9%), the calibrations of both risk scores were acceptable (both p for Hosmer-Lemeshow test >0.25). The AUCs of the first and second risk scores were 0.710 (95% CI: 0.680 to 0.741) and 0.712 (95% CI: 0.682 to 0.743), respectively (p for difference: 0.9273).

CONCLUSION

Both developed risk scores had adequate performance for the prediction of GDM in Chinese pregnant women in Tianjin, China. Further validations are needed to evaluate their performance in other populations and using different methods to identify GDM cases.

Multiple metal concentrations and gestational diabetes mellitus in Taiyuan, China

BACKGROUND

The association between multiple metal concentrations and gestational diabetes mellitus (GDM) is poorly understood.

METHODS

A total of 776 women with GDM and an equal number of controls were included in the study. Concentrations of metals in participants' blood (nickel (Ni), arsenic (As), cadmium (Cd), antimony (Sb), thallium (Tl), mercury (Hg), lead (Pb)) were measured using inductively coupled plasma-mass. We used unconditional logistical regression models to estimate the associations between metals and GDM. We also employed weighted quantile sum (WQS) regression and principal components analysis (PCA) to examine metal mixtures in relation to GDM.

RESULTS

An increased risk of GDM was associated with As (OR = 1.49, 95% CI: 1.11, 2.01 for the 2nd tertile vs. the 1st tertile) and Hg (OR = 1.43, 95% CI: 1.09, 1.88 for the 3rd tertile vs. the 1st tertile). In WQS analysis, the WQS index was significantly associated with GDM (OR = 1.20, 95% CI: 1.02, 1.41). The major contributor to the metal mixture index was Hg (69.2%), followed by Pb (12.8%), and As (11.3%). Based on PCA, the second principal component, which was characterized by Hg, Ni, and Pb, was associated with an increased risk of GDM (OR = 1.46, 95% CI: 1.02, 2.08 for the highest quartile vs. the lowest quartile).

CONCLUSIONS

Our study results suggest that high metal levels are associated with an increased risk of GDM, and this increased risk is mainly driven by Hg and, to a lesser extent, by Ni, Pb, and As.

The Effect of Strict Volume Control Assessed by Repeated Bioimpedance Spectroscopy on Cardiac Function in Peritoneal Dialysis Patients

Adequate fluid management plays an important role in decreasing cardiovascular risk in peritoneal dialysis (PD) patients. We evaluated whether strict volume control monitored by bioimpedance spectroscopy (BIS) affects cardiac function in PD patients. This study is a secondary analysis of a multicentre, prospective, randomized, controlled trial. Fluid overload was assessed by the average overhydration/extracellular water (OH/ECW) at baseline, 6 months and 12 months. Patients were categorized as time-averaged overhydrated (TA-OH/ECW ≥15%) or normohydrated (TA-OH/ECW <15%), and echocardiographic parameters were compared between groups. Among a total of 151 patients, 120 patients exhibited time-averaged normohydration. Time-averaged overhydrated patients had a significantly higher left atrial (LA) diameter and E/e′ ratio and a lower left ventricular (LV) ejection fraction at 12 months than time-averaged normohydrated patients. LA diameter, end-systolic volume and end-diastolic volume were decreased at 12 months compared to baseline in time-averaged normohydrated patients only. TA-OH/ECW was independently associated with ejection fraction at 12 months (β = −0.190; p = 0.010). TA-OH/ECW, but not OH/ECW at 12 months, was an independent risk factor for LV dysfunction (odds ratio 4.020 [95% confidence interval 1.285–12.573]). Overhydration status based on repeated BIS measurements is an independent predictor of LV systolic function in PD patients.

Maternal height and risk of gestational diabetes: a systematic review and meta-analysis

AIMS

Identifying women at high risk of developing gestational diabetes mellitus (GDM) is a public health interest. This study aims to investigate the association between maternal height and risk of GDM through meta-analysis.

METHODS

We retrieved the studies that assessed maternal height in relation to GDM. Pooled risk estimates of the included articles and their 95% confidence intervals (95% CIs) were calculated using a fixed- or random-effects model. Subgroup analyses were conducted according to study design and study location. Quality of studies was determined using the Newcastle-Ottawa Scale. Publication bias was detected using the Egger's and Begg's tests.

RESULTS

A total of 10 studies including 7 cohort and 3 cross-sectional studies with a total of 126,094 women were included for meta-analysis. Combined, each 5-cm increase in height was associated with about 20% reduction in risk of GDM [pooled odds ratio = 0.80, (95% CI 0.76, 0.85)]. The analysis revealed high heterogeneity between studies which dissolved after subgroup analysis by study design. This significant association did not differ between Asian and non-Asian populations. Egger's and Begg's tests showed little evidence of publication bias.

CONCLUSIONS

The present meta-analysis supports the conception that short stature is associated with GDM. Further studies of high quality are needed to confirm the findings.