1.
Gut Microbiota Serves a Predictable Outcome of Short-Term Low-Carbohydrate Diet (LCD) Intervention for Patients with Obesity.
Zhang, S, Wu, P, Tian, Y, Liu, B, Huang, L, Liu, Z, Lin, N, Xu, N, Ruan, Y, Zhang, Z, et al
Microbiology spectrum. 2021;(2):e0022321
Abstract
To date, much progress has been made in dietary therapy for obese patients. A low-carbohydrate diet (LCD) has reached a revival in its clinical use during the past decade with undefined mechanisms and debatable efficacy. The gut microbiota has been suggested to promote energy harvesting. Here, we propose that the gut microbiota contributes to the inconsistent outcome under an LCD. To test this hypothesis, patients with obesity or patients who were overweight were randomly assigned to a normal diet (ND) or an LCD group with ad libitum energy intake for 12 weeks. Using matched sampling, the microbiome profile at baseline and end stage was examined. The relative abundance of butyrate-producing bacteria, including Porphyromonadaceae Parabacteroides and Ruminococcaceae Oscillospira, was markedly increased after LCD intervention for 12 weeks. Moreover, within the LCD group, participants with a higher relative abundance of Bacteroidaceae Bacteroides at baseline exhibited a better response to LCD intervention and achieved greater weight loss outcomes. Nevertheless, the adoption of an artificial neural network (ANN)-based prediction model greatly surpasses a general linear model in predicting weight loss outcomes after LCD intervention. Therefore, the gut microbiota served as a positive outcome predictor and has the potential to predict weight loss outcomes after short-term LCD intervention. Gut microbiota may help to guide the clinical application of short-term LCD intervention to develop effective weight loss strategies. (This study has been registered at the China Clinical Trial Registry under approval no. ChiCTR1800015156). IMPORTANCE Obesity and its related complications pose a serious threat to human health. Short-term low-carbohydrate diet (LCD) intervention without calorie restriction has a significant weight loss effect for overweight/obese people. Furthermore, the relative abundance of Bacteroidaceae Bacteroides is a positive outcome predictor of individual weight loss after short-term LCD intervention. Moreover, leveraging on these distinct gut microbial structures at baseline, we have established a prediction model based on the artificial neural network (ANN) algorithm that could be used to estimate weight loss potential before each clinical trial (with Chinese patent number 2021104655623). This will help to guide the clinical application of short-term LCD intervention to improve weight loss strategies.
2.
High risk of metabolic syndrome after delivery in pregnancies complicated by gestational diabetes.
Shen, Y, Li, W, Leng, J, Zhang, S, Liu, H, Li, W, Wang, L, Tian, H, Chen, J, Qi, L, et al
Diabetes research and clinical practice. 2019;:219-226
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Abstract
AIMS: To investigate the risk of postpartum metabolic syndrome in women with GDM compared with those without GDM in a Chinese population. METHODS Tianjin GDM observational study included 1263 women with a history of GDM and 705 women without GDM. Multivariate logistic regression was used to assess risks of postpartum metabolic syndrome between women with and without GDM. Postpartum metabolic syndrome was diagnosed by two commonly used criteria. RESULTS During a mean 3.53 years of follow up, 256 cases of metabolic syndrome were identified by using the NCEP ATPIII criteria and 244 cases by using the IDF criteria. Multivariable-adjusted odds ratios of metabolic syndrome in women with GDM compared with those without GDM were 3.66 (95% confidence interval [CI] 2.02-6.63) for NCEP ATPIII criteria and 3.90 (95% CI 2.13-7.14) for IDF criteria. Women with GDM had higher multivariable-adjusted odds ratios of central obesity, hypertriglyceridemia, and high blood pressure than women without GDM. The multivariable-adjusted odds ratios of low HDL cholesterol and hyperglycemia were not significant between women with and without GDM, however, the multivariable-adjusted odds ratio of hyperglycemia became significant when we used the modified criteria. CONCLUSIONS The present study indicated that women with prior GDM had significantly higher risks for postpartum metabolic syndrome, as well as its individual components.
3.
Global warming and obesity: a systematic review.
An, R, Ji, M, Zhang, S
Obesity reviews : an official journal of the International Association for the Study of Obesity. 2018;(2):150-163
Abstract
Global warming and the obesity epidemic are two unprecedented challenges mankind faces today. A literature search was conducted in the PubMed, Web of Science, EBSCO and Scopus for articles published until July 2017 that reported findings on the relationship between global warming and the obesity epidemic. Fifty studies were identified. Topic-wise, articles were classified into four relationships - global warming and the obesity epidemic are correlated because of common drivers (n = 21); global warming influences the obesity epidemic (n = 13); the obesity epidemic influences global warming (n = 13); and global warming and the obesity epidemic influence each other (n = 3). We constructed a conceptual model linking global warming and the obesity epidemic - the fossil fuel economy, population growth and industrialization impact land use and urbanization, motorized transportation and agricultural productivity and consequently influences global warming by excess greenhouse gas emission and the obesity epidemic by nutrition transition and physical inactivity; global warming also directly impacts obesity by food supply/price shock and adaptive thermogenesis, and the obesity epidemic impacts global warming by the elevated energy consumption. Policies that endorse deployment of clean and sustainable energy sources, and urban designs that promote active lifestyles, are likely to alleviate the societal burden of global warming and obesity.