The relationship between dietary protein consumption and the risk of type 2 diabetes (T2D) has been inconsistent. The aim of this meta-analysis was to explore the relations between dietary protein consumption and the risk of T2D. We conducted systematic retrieval of prospective studies in PubMed, Embase, and Web of Science. Summary relative risks were compiled with a fixed effects model or a random effects model, and a restricted cubic spline regression model and generalized least squares analysis were used to evaluate the diet–T2D incidence relationship. T2D risk increased with increasing consumption of total protein and animal protein, red meat, processed meat, milk, and eggs, respectively, while plant protein and yogurt had an inverse relationship. A non-linear association with the risk for T2D was found for the consumption of plant protein, processed meat, milk, yogurt, and soy. This meta-analysis suggests that substitution of plant protein and yogurt for animal protein, especially red meat and processed meat, can reduce the risk for T2D.

Background: The epidemiological evidence on the association of sleep quality on anxiety symptoms has been inconclusive. This study aimed to explore the association between sleep quality and anxiety symptoms in rural Chinese population and investigate whether age, lifestyles, and chronic diseases modified this association.Methods: A total of 27,911 participants aged 18–79 years from the Henan Rural Cohort Study were included in the study. Sleep quality was assessed using the Pittsburgh Sleep Quality Index (PSQI) scale. Poor sleep quality was defined as PSQI ≥6. Anxiety symptoms were evaluated with the two-item generalized anxiety disorder scale (GAD-2). Individual with score ≥ 3 was viewed as having anxiety symptoms. Logistic regression and restricted cubic spline were conducted to examine the association of sleep quality with anxiety symptoms.Results: Altogether, 6087 (21.80%) participants were poor sleepers and 1557 (5.58%) had anxiety symptoms. The odds of anxiety were increased with increment of PSQI score after fitting restricted cubic splines. The poor sleep quality was associated with a higher possibility of anxiety symptoms [odd ratio (OR): 4.60, 95% confidence interval (CI): 3.70–5.72] in men, and (OR: 3.56, 95% CI: 3.10–4.09) in women for multivariable analysis. Further, stratified analyses showed that the effect of sleep quality on anxiety symptoms could be modified by age, marital status, smoking status, drinking status, hypertension, and type 2 diabetes mellitus.Conclusions: A dose-response association between PSQI score and anxiety symptoms was found. In addition, the relationship between poor sleep quality and greater anxiety symptoms was observed in this rural population, especially in participants aged ≥60 years and those with unhealthy habits or had a chronic disease.Trial registration: The trial was prospectively registered on July 6, 2015 and available online at ClinicalTrials.gov ID:ChiCTR-OOC-15006699.

Population-based studies on the associations of long-term exposure to particulate matter (PM) with androgen and progesterone are still scant. Residential greenness is benefits health by promoting physical activity, reducing air pollution, and improving mental health, but it remains unclear whether it is related to androgen and progesterone levels among humans. This study aimed to explore the individual and interactive effects of PM and residential greenness on serum testosterone and progesterone levels among rural Chinese adults. A total of 6017 subjects were recruited from the baseline of the Henan Rural Cohort Study in 2016. Serum testosterone and progesterone were measured with liquid chromatography-tandem mass spectrometry. Particulate matters (PM) (PM1, PM2.5, and PM10) were assessed by machine learning algorithms. Residential greenness was assessed using the normalized difference vegetation index (NDVI) within 500-m, 1000-m, and 3000-m buffers around participants' residences. The effects of air pollutants and residential greenness and their interaction on serum testosterone and progesterone levels were assessed using linear mixed-effects models with township as a random intercept. After adjusting for potential confounding factors, a 1 μg/m3 increase in PM2.5 or PM10 was associated with a 0.037 or 0.030 ng/ml increase in serum testosterone, respectively, in females and with a 0.111 or 0.182 ng/ml decrease in serum progesterone, respectively, in males. A 1 μg/m3 increase in PM1, PM2.5 or PM10 was associated with a 0.222, 0.306, or 0.295 ng/ml decrease in serum progesterone, respectively, among females. Moreover, a 0.1-unit increase in NDVI was associated with a 0.310 ng/ml increase in serum testosterone and a 0.170 ng/ml increased in serum progesterone in males, as well as with a 0.143 ng/ml increase in serum progesterone in females. Interaction effects of PM and residential greenness on serum testosterone and progesterone levels were observed, indicating that the effects of residential greenness on serum testosterone and progesterone were modified by high levels of PM. In addition, physical activity significantly mediated 2.92% of the estimated association between greenness and testosterone levels. Our study suggested that long-term exposure to PM was positively associated with serum testosterone in males but negatively associated with progesterone levels in both genderssin. In addition, positive associations of residential greenness with serum testosterone and progesterone levels were observed, but they were modified by high levels of PM. Furthermore, the estimated effects of residential greenness on testosterone levels were partly mediated by physical activity.