BackgroundThe sleep quality of pregnant women in the third trimester is related to mental health. However, there is still a lack of large-scale cohort research exploring this relationship in the second trimester. Thus, we assessed the associations of sleep quality during the second trimester with antenatal stress and antenatal and postnatal depression.MethodsWe examined 1152 pregnant women from a prospective cohort study in China to assess the associations of sleep quality in the second trimester with antenatal stress, antenatal depression, and postnatal depression. We used linear regression models and logistic regression models to examine the associations of sleep quality (Pittsburgh Sleep Quality Index [PSQI]) during pregnancy with perinatal stress (Pregnancy Pressure Scale [PPS]) and depression (Edinburgh Postnatal Depression Scale [EPDS]) status. We further assessed the relationship in groups divided according to maternal age.ResultsPSQI scores were positively associated with antenatal PPS scores (β: 1.52, 95% confidence interval [CI]: 1.28, 1.76), antenatal EPDS scores (β: 0.68, 95% CI: 0.58, 0.78), and postpartum EPDS scores (β: 0.51, 95% CI: 0.38, 0.64). Poor sleep quality (PSQI scores ≥5) was associated with antenatal stress status (odds ratio [OR]: 2.60, 95% CI: 1.79, 3.77), antenatal depression status (OR: 3.42, 95% CI: 2.48, 4.72), and postpartum depression status (OR: 2.40, 95% CI: 1.58, 3.64) after adjusting maternal age, BMI, gestational age, smoking, educational level, annual household income and social support. The association of poor sleep quality (PSQI scores ≥5) in the second trimester with postnatal depression status was significant among women more than or equal to 30 years old (OR: 4.12, 95% CI: 2.18, 7.78) but not among women less than 30 years old after adjusting covariates above.ConclusionPoor sleep quality in the second trimester among Chinese pregnant women is associated with stress and depression symptoms. Strategies to boost sleep quality should be considered during prenatal health care to improve women’s mental health status.

Respiratory tract microbiome is closely related to respiratory tract infections, while characterization of oropharyngeal microbiome in recovered coronavirus disease 2019 (COVID-19) patients is not studied. Herein, oropharyngeal swabs are collected from confirmed cases (CCs) with COVID-19 (73 subjects), suspected cases (SCs) (36), confirmed cases who recovered (21), suspected cases who recovered (36), and healthy controls (Hs) (140) and then completed MiSeq sequencing. Oropharyngeal microbial 𝜶-diversity is markedly reduced in CCs versus Hs. Opportunistic pathogens are increased, while butyrate-producing genera are decreased in CCs versus Hs. The classifier based on eight optimal microbial markers is constructed through a random forest model and reached great diagnostic efficacy in both discovery and validation cohorts. Notably, the classifier successfully diagnosed SCs with positive IgG antibody as CCs and is demonstrated from the perspective of the microbiome. Importantly, several genera with significant differences gradually increase and decrease along with recovery from COVID-19. Forty-four oropharyngeal operational taxonomy units (OTUs) are closely correlated with 11 clinical indicators of SARS-CoV-2 infection and Hs based on Spearman correlation analysis. Together, this research is the first to characterize oropharyngeal microbiota in recovered COVID-19 cases and suspected cases, to successfully construct and validate the diagnostic model for COVID-19 and to depict the correlations between microbial OTUs and clinical indicators.

Background The Lancet Commission on Global Surgery established the Three Delays framework, categorising delays in accessing timely surgical care into delays in seeking care (First Delay), reaching care (Second Delay), and receiving care (Third Delay). Globally, knowledge gaps regarding delays for fracture care, and the lack of large prospective studies informed the rationale for our international observational study. We investigated delays in hospital admission as a surrogate for accessing timely fracture care and explored factors associated with delayed hospital admission. MethodsIn this prospective observational substudy of the ongoing International Orthopaedic Multicenter Study in Fracture Care (INORMUS), we enrolled patients with fracture across 49 hospitals in 18 low-income and middle-income countries, categorised into the regions of China, Africa, India, south and east Asia, and Latin America. Eligible patients were aged 18 years or older and had been admitted to a hospital within 3 months of sustaining an orthopaedic trauma. We collected demographic injury data and time to hospital admission. Our primary outcome was the number of patients with open and closed fractures who were delayed in their admission to a treating hospital. Delays for patients with open fractures were defined as being more than 2 h from the time of injury (in accordance with the Lancet Commission on Global Surgery) and for those with closed fractures as being a delay of more than 24 h. Secondary outcomes were reasons for delay for all patients with either open or closed fractures who were delayed for more than 24 h. We did logistic regression analyses to identify risk factors of delays of more than 2 h in patients with open fractures and delays of more than 24 h in patients with closed fractures. Logistic regressions were adjusted for region, age, employment, urban living, health insurance, interfacility referral, method of transportation, number of fractures, mechanism of injury, and fracture location. We further calculated adjusted relative risk (RR) from adjusted odds ratios, adjusted for the same variables. This study was registered with ClinicalTrials.gov, NCT02150980, and is ongoing. Findings Between April 3, 2014, and May 10, 2019, we enrolled 31 255 patients with fractures, with a median age of 45 years (IQR 31-62), of whom 19 937 (63•8%) were men, and 14 524 (46•5%) had lower limb fractures, making them the most common fractures. Of 5256 patients with open fractures, 3778 (71•9%) were not admitted to hospital within 2 h. Of 25 999 patients with closed fractures, 7141 (27•5%) were delayed by more than 24 h. Of all regions, Latin America had the greatest proportions of patients with delays (173 [88•7%] of 195 patients with open fractures; 426 [44•7%] of 952 with closed fractures). Among patients delayed by more than 24 h, the most common reason for delays were interfacility referrals (3755 [47•7%] of 7875) and Third Delays (cumulatively interfacility referral and delay in emergency department: 3974 [50•5%]), while Second Delays ...

Dietary patterns during pregnancy have been shown to influence the development of gestational diabetes mellitus (GDM). However, evidence from Asian populations is limited and inconsistent. We conducted a prospective cohort study in China to assess the relationship between dietary patterns and GDM. We administered three-day food diaries (TFD) and food frequency questionnaires (FFQ) at the second trimester. GDM was diagnosed with a 75 g 2-h oral glucose tolerance test at 24–28 weeks of gestation. We identified dietary patterns using principal components analysis and used multivariable logistic regression to investigate associations of dietary patterns with GDM. Of the 1014 participants, 23.5% were diagnosed with GDM. Both the TFD and FFQ identified a “traditional pattern”, consisting of high vegetable, fruit, and rice intake, which was associated with a lower GDM risk (odds ratio (OR) for quartile 4 versus quartile 1: 0.40, 95% CI: 0.23–0.71 for traditional pattern (TFD); OR: 0.44, CI: 0.27–0.70 for traditional pattern (FFQ)). The protective associations were more pronounced among women ≥35 years old. A whole grain–seafood TFD pattern was associated with higher risk of GDM (OR: 1.73, 95% CI: 1.10–2.74). These findings may provide evidence for making dietary guidelines among pregnant women in Chinese populations to prevent GDM.