BACKGROUND:Adverse childhood experiences (ACEs) are known risk factors for mental health issues in adulthood. Shift workers, especially those in high-stress roles like aviation, are particularly vulnerable to these mental health conditions. However, limited research has explored the relationship between ACE exposure and mental health in this population. METHODS:This cross-sectional study used data from the Civil Aviation Health Cohort of China (November to December 2023). Aviation personnel (aged 18-60) reported 11 ACE types, categorized by count and latent class analysis. Mental health symptoms were assessed using the Patient Health Questionnaire-9 (PHQ-9), the Generalized Anxiety Disorder-7 (GAD-7), and a single-item screener for depression, anxiety, and suicidal ideation, respectively. RESULTS:The study analyzed 19,137 aviation personnel (61.7% male, mean age 31.7 years). Latent class analysis identified three ACE patterns: low ACE (96.5%), abuse (2.8%), and family dysfunction (0.7%). Notably, 22.6% reported ≥1 ACE and 1.2% reported ≥4, showing a dose-response association with mental health risks. Family dysfunction showed the strongest associations with depression (AOR 5.22, 95% CI 3.80-7.17), anxiety (AOR 3.94, 95% CI 2.82-5.50), and suicidal ideation (AOR 4.46, 95% CI 2.55-7.82). LIMITATIONS:The cross-sectional design precludes causal inference. The reliance on retrospective self-report of ACEs may be subject to recall bias. Potential residual confounding and selection bias further limit generalizability. CONCLUSIONS:These findings highlight the need for workplace mental health strategies to support shift workers, particularly those with a history of ACEs. Further research is needed on mechanisms linking ACEs to aviation shift workers' mental health and potential protective factors.

The relationship among childhood trauma, borderline personality traits and self-control in adolescents has been established, but the specific impact of each type of childhood trauma remains to be elucidated. This study aims to explore how different types of childhood trauma are associated with borderline personality traits and self-control among adolescents in China. A cross-sectional study was conducted on 2,664 adolescents (M = 16.54 years, SD = 0.95) from a senior high school in Henan, China. Childhood Trauma Questionnaire-Short Form, Borderline Personality Dimension of Personality Diagnostic Questionnaire-4 and Self-Control Scale were used to evaluate childhood trauma, borderline personality traits, and self-control. The prevalence of borderline personality traits in Chinese adolescents was 12.00

AIMS:The mental health risk factors for primary healthcare workers (PHWs) following the Coronavirus Disease 2019 pandemic and the differences by urbanicity remain unclear. In this study, we aimed to identify key factors of anxiety and depression among PHWs in urban and rural settings in China. METHODS:This cross-sectional study was conducted in all 31 provinces in mainland China, between 1 May and 31 October 2022. A total of 3,769 PHWs, including family physicians, nurses, public health professionals, pharmacists, and other medical staff, were recruited from 44 urban community health service centers and 27 rural township hospitals. The Bayesian Additive Regression Tree model was employed to identify risk factors of anxiety and depression. RESULTS:Among 3,769 PHWs, 1,006 (26.7%) worked in urban areas and 2,763 (73.3%) in rural areas. Occupational satisfaction significantly influenced anxiety in both urban and rural practitioners. For urban PHWs, living with family (odds ratio (OR): 0.42, 95% confidence interval (CI): 0.28-0.62) and self-rated health (fair: OR: 0.31, 95% CI: 0.23-0.42; good: OR: 0.13, 95% CI: 0.09-0.20) were key factors of anxiety. For rural PHWs, after-work exercise (rarely: OR: 0.28, 95% CI: 0.11-0.76; frequently: OR: 0.15, 95% CI: 0.05-0.44) played a critical role. Depression was associated with after-work exercise, self-rated health, and occupational satisfaction for all PHWs. Additionally, living with family (OR: 0.51, 95% CI: 0.34-0.75) and organizational support satisfaction (satisfied: OR: 0.28, 95% CI: 0.19-0.42) were significant for urban practitioners. CONCLUSIONS:Risk factors such as occupational satisfaction, health, and family relations significantly influence PHW mental health in China, with notable differences by urbanicity. Tailored mental health interventions are recommended to address urban-rural disparities.

The primary protein components of white matter include myelin basic protein (MBP) and 2’,3’-cyclic nucleotide 3’-phosphodiesterase (CNP). Alterations in their expression are significantly implicated in depression. This study investigated changes in MBP and CNP expression associated with depressive-like behaviors induced by chronic unpredictable stress (CUS) and evaluated therapeutic interventions using fluoxetine (FLU), an enriched environment (EE), or their combination. Male Sprague Dawley rats were randomly assigned to a control group and four CUS-exposed groups undergoing 6 weeks of stress. During the final 3 weeks of CUS, rats received daily fluoxetine (CUS + FLU group), were housed in EE (CUS + EE group), or received combined EE and fluoxetine (CUS + FLU + EE group). Depression-like behaviors were assessed through sucrose preference, forced swimming, and open field tests after CUS completion and at the end of weeks 4–6. Protein and mRNA expression levels of MBP and CNP in the prefrontal cortex were quantified via immunohistochemistry, western blot, and qRT-PCR. Three weeks following CUS exposure, rats demonstrated significant depression-like behavioral phenotypes. By the fifth week, these behavioral deficits were ameliorated in the CUS + FLU + EE, whereas the CUS + FLU and CUS + EE groups exhibited comparable behavioral recovery by week 6. Parallel molecular analyses revealed diminished protein and mRNA expression levels of MBP and CNP in the prefrontal cortex of CUS-exposed animals, accompanied by a pronounced elevation in IL-1β expression. Therapeutic interventions with FLU, EE, or their combination significantly attenuated these CUS-induced molecular alterations. The antidepressant effects correlated with restored MBP, CNP, and IL-1β expression levels, suggesting that MBP/CNP deficiencies in depression may involve IL-1β elevation. In particular, combined enriched environment and fluoxetine accelerated behavioral recovery.

Hospitals are high risk areas for the spread of diseases, with indoor bioaerosols containing a variety of pathogens. Inhalation of these pathogens may cause severe nosocomial infections in patients and medical staff. A comprehensive investigation was conducted during the influenza A outbreak to explore the distribution and pathogenic risk of airborne pathogens and antibiotic resistance genes (ARGs) across different hospital departments. It was revealed that airborne bacterial concentrations ranged from 118 to 259 CFU/m3, and the main aerosol particle size was 4.7-5.8 μm (27.7 %). The proportion of bioaerosols smaller than 2.5 μm was highest in the respiratory waiting area (59.3 %). The dominant pathogens detected in hospital air were Bacillus, Staphylococcus, Pseudomonas and Micrococcus. The absolute abundance of ARGs/mobile genetic elements (MGEs) ranged from 0.55 to 479.44 copies/m3, peaking in the respiratory ward air. TetL-02, lnuA-01, intI1, ermB, and qacEdelta1-02 were the top five ARGs/MGEs in hospital air. Moreover, doctors inhaled higher doses of ARGs/MGEs in inpatient wards than outpatient waiting areas. Network analysis identified Pseudomonas, Micrococcus, Microbacterium, and Enterobacter as potential ARGs reservoirs. The Bugbase result showed the presence of potentially pathogenic pathogens in the bioaerosols at all sampling sites. The quantitative microbiological risk assessment results further showed that airborne Staphylococcus could pose an infection risk to medical staff. It was determined that the use of masks was effective in reducing this risk to an acceptable level. This study will provide a scientific basis for comprehensively understanding the characteristics and potential risks of hospital bioaerosols during the outbreak of respiratory infectious diseases.

OBJECTIVE:To explore the early clinical efficacy of a three-stage external treatment with traditional Chinese medicine (TCM) in the treatment of talar bone contusion caused by acute ankle sprain. METHODS:A retrospective analysis was performed on 360 patients with primary lateral ankle sprain admitted from September 2021 to July 2024. Patients with talar bone contusion were selected based on MRI examination, and 73 cases were finally included. According to different treatment methods, they were divided into the observation group and the control group. The observation group consisted of 35 cases, including 16 males and 19 females, aged 24 to 37 years old with an average of (30.34±2.68) years old, and received the three-stage external TCM treatment combined with the "POLICE" protocol. The control group included 38 cases, including 18 males and 20 females, aged 24 to 35 years old with an average of (29.87±2.57) years old, and was treated with the "POLICE" protocol alone. The volume of bone marrow edema (BME) area shown by MRI before treatment and 6 weeks after treatment was measured using 3D Slicer software, and the BME improvement rate was calculated. The "Figure of 8" measurement method was used to assess ankle swelling before treatment and at 1 and 3 weeks after treatment. The visual analogue scale (VAS) was used to evaluate ankle pain before treatment and at 1 and 6 weeks after treatment. At 6 weeks after treatment, the American Orthopaedic Foot and Ankle Society (AOFAS) ankle-hindfoot score and Karlsson ankle function score system were used to evaluate the improvement of ankle function. RESULTS:A total of 73 patients with talar bone contusion caused by ankle sprain completed the 6-week follow-up. At 6 weeks after treatment, the BME improvement rate in the observation group was (39.18±0.06)%, which was higher than (26.75±0.03)% in the control group, with a statistically significant difference (P<0.05). After 1 week of treatment, the VAS score in the observation group was (2.89±0.72) points, lower than (3.37±0.79) points in the control group, and the difference was statistically significant (P<0.05). The ankle swelling degree in the observation group was (50.20±3.19) cm, lower than (52.00±3.60) cm in the control group, with a statistically significant difference (P<0.05). After 3 weeks of treatment, there was no statistically significant difference in ankle swelling between the two groups. At 6 weeks after treatment, there was no statistically significant difference in VAS scores between the two groups. At 6 weeks after treatment, the AOFAS ankle-hindfoot score and Karlsson score in the observation group were (87.43±4.18) and (82.77±5.93) points, respectively, which were higher than (82.92±4.87) and (76.45±6.85) points in the control group, with statistically significant differences (P<0.05). According to the AOFAS ankle-hindfoot score, 8 cases were excellent and 27 cases were good in the observation group;2 cases were excellent, 33 cases were good, and 3 cases were fair in the control group. The difference between the two groups was statistically significant (χ2=7.089, P=0.029). CONCLUSION:The three-stage external TCM treatment combined with the "POLICE" protocol has a significant early clinical efficacy. It can significantly reduce ankle pain and swelling in patients with bone contusion caused by acute lateral ankle sprain, promote the absorption of bone marrow edema, and accelerate the recovery of ankle function.

Accurate psychiatric diagnosis and assessment are crucial for effective treatment. However, current diagnostic approaches heavily rely on subjective observations constrained by time and clinical resources. This study investigates the potential of using Large Language Models (LLMs) to identify the symptoms in psychiatrist-patient dialogues and use them as intermediate features to predict the diagnostic labels. We collected audio recordings of 1160 outpatients with depressive disorder and anxiety disorder. LLMs were trained and utilized to identify clinical symptoms, rate assessment scales, and an ensemble learning pipeline was designed to classify diagnostic results and symptoms with 10-fold cross-validation. The system achieved 86.9% accuracy for identifying the appearance of clinical annotations and 74.7% (77.2%) accuracy for identifying symptoms of anxiety (depression). In addition, analysis of LLM-generated features shows that depression cases exhibited prominent markers of anhedonia and decreased volition, whereas anxiety disorders were characterized by tension and an inability to relax.

Conversational agents have emerged as promising tools for depression-diagnosis-oriented chats. However, the integration of task-oriented dialogues with empathetic chit-chat in diagnostic interactions presents significant challenges. Such unique requirements demand professional expertise and empathetic communication, pushing beyond the capabilities of traditional dialogue frameworks designed for single optimization objectives. To bridge this gap, we propose a novel ontology-driven framework specifically designed for depression diagnosis dialogues. Our approach unifies the precision of task-oriented interactions with the empathetic nuance of chit-chat, enabling a more balanced and effective diagnostic exchange. We apply this framework to D4, the only publicly available Chinese dialogue dataset focused on depression diagnosis. Extensive experimental results demonstrate notable improvements in all tasks, highlighting the potential of our approach to advance task-oriented dialogue systems in digital mental health applications.

Objective To explore the relationship between bedtime procrastination and fear of missing out and the intervention effect of aerobic exercise on bedtime procrastination,so as to provide a theoretical basis and practical reference for remedying bedtime procrastination.Methods Totally 988 students were selected through random sampling and then surveyed with the bedtime procrastination scale and the fear of missing out scale.Correlation and regression analyses were performed to explore the relationship between bedtime procrastination and fear of missing out.A total of 36 students were recruited from the 988 students to participate in the exercise intervention and they were assigned into an exercise group and a control group by the random number table method,with 18 students in each group.The exercise group performed aerobic exercise for 12 weeks,while the control group maintained daily activities.The participants' scores on the bedtime procrastination scale and the fear of missing out scale were recorded before and after the intervention and compared.Results The fear of missing out was positively correlated with bedtime procrastination among college students(r=0.214,P<0.001),and it was an important predictive factor for bedtime procrastination(β=0.241,P<0.001).After the intervention,the scores of bedtime procrastination scale decreased in the exercise group(t=2.277,P=0.036),while there was no significant difference in the scores of the control group before and after intervention(t=-0.787,P=0.442).Conclusions A high level of fear of missing out indicates severe bedtime procrastination.And 12-week exercise intervention could remedy bedtime procrastination.

Purpose:This study aims to explore global, regional, and national trends in the prevalence of depression and disability-adjusted life years (DALYs) among women of childbearing age from 1990 to 2021, as well as to project future trends from 2022 to 2040. Methods:This research analyzes the prevalence of depression and Disability-Adjusted Life Years (DALYs) among Women of Childbearing Age (WCBA) using data from the Global Burden of Disease (GBD) database, covering the period from 1990 to 2021. We evaluate trends in the burden of depression in WCBA through estimated annual percentage change (EAPC) and percentage change, as well as annual percentage change (APC) and average annual percentage change (AAPC) derived from Joinpoint regression analyses. Additionally, we employ age-period-cohort modeling to provide a more comprehensive evaluation of the prevalence of WCBA and the burden of DALYs, including future projections. Results:In 2021, it was estimated that there were 121.24 million cases of depression among women of childbearing age worldwide, with disability-adjusted life years (DALYs) accounting for 21.04 million cases. When compared to figures from 1990, these numbers indicate percentage increases of 68% and 69%, respectively. Moreover, despite an overall increase in both global prevalence and DALY rates, this rise was not considered statistically significant, as reflected by an estimated annual percentage change (EAPC) of -0.02 (95% confidence interval: -0.17 to 0.13) for prevalence and -0.06 (95% CI: -0.24 to 0.12) for DALYs. Furthermore, the average annual percentage change (AAPC) was computed to be 0.4789 (95% CI: 0.3289-0.6295; P < 0.001) for prevalence and 0.524 (95% CI: 0.3756-0.6725; P < 0.001) for DALYs. Projections made using our Bayesian age-period-cohort (BAPC) model suggest that we can expect a considerable increase in the global prevalence of depression and DALY rates among women of childbearing age by the year 2040.

Dry eye disease (DED) is one of the most common ocular surface disorders caused by various contributors. Air pollutants are considered a risk factor for ocular surface diseases. We aimed to investigate the associations between air pollutants (PM2.5, PM10, NO2, SO2, CO and O3) and PM2.5 constituents and daily outpatient visits for DED, as well as the modifying effect of temperature on the associations. Daily data on DED outpatient visits and environmental variables during 2014–2019 were collected in Hangzhou, China. Distributed lag nonlinear models (DLNM) combined with time-stratified case-crossover design were utilized to evaluate the effects of air pollutants and PM2.5 constituents on DED daily outpatient visits during 0‒3 lag days. Furthermore, we also estimated the modification effect of temperature stratified by median. The attributable fraction (AF) of air pollutants and PM2.5 constituents on DED outpatient visits were quantified. Stratified analyses of gender, age, and seasons were conducted to assess vulnerable population characteristics and high-risk periods. Every interquartile range increase in PM2.5, PM10, NO2, SO2 and CO concentration were significantly associated with daily DED cases. The AF were 6.42

The efficacy of Jingu Tongluo Granules in treating acute lateral ankle ligament injuries is remarkable,however,accurately assessing its clinical efficacy remains challenging.Therefore,a machine learning-based prediction model for the therapeutic efficacy of Jingu Tongluo Granules in treating acute lateral ankle ligament injuries was developed using Delta-radiomics.The study involved 107 patients with acute anterior talofibular ligament injuries who received treatment for two weeks with topical Jingu Tongluo Granules based on the protection,optimal load,ice,compression,elevation(POLICE)principle.The patients were divided into an excellent efficacy group(71 cases)and a poor efficacy group(36 cases)according to their American Orthopedic Foot and Ankle Society(AOFAS)scores.The data was further divided into a training set and a validation set in 7∶3.Radiomics features strongly correlated with anterior talofibular ligament injury were extracted and selected from transverse ankle magnetic resonance imaging performed before and after treatment.Light gradient boosting machine(LightGBM)classifier was employed to develop the pre-treatment,post-treatment,and Delta-radiomics models.The clinical utility and predictive performance of each model were evaluated using the receiver operating characteristic curve(ROC),decision curve analysis(DCA),and calibration curves.A total of 1 197 radiomics features were extracted,and after feature selection and dimensionality reduction,4,13,and 8 radiomics features from pre-treatment,post-treatment,and Delta,respectively,were retained to construct machine learning models using LightGBM.The LightGBM model based on Delta-radiomics features demonstrated the optimal predictive performance,with AUC of 0.917(95％CI[0.856,0.979])and 0.863(95％CI[0.729,0.998])for the training and validation sets,respectively.Both the DCA and calibration curves indicated favorable prediction performance.The LightGBM machine learning model based on Delta-radiomics is effective in predicting the therapeutic efficacy of Jingu Tongluo Granules in treating acute anterior talofibular ligament injuries.

ObjectivesHip involvement is an important reason of disability in patients with ankylosing spondylitis (AS). Unveiling the potential phenotype of hip involvement in AS remains an unmet need to understand its biological mechanisms and improve clinical decision-making. Radiomics, a promising quantitative image analysis method that had been successfully used to describe the phenotype of a wide variety of diseases, while it was less reported in AS. The objective of this study was to investigate the feasibility of radiomics-based approach to profile hip involvement in AS.MethodsA total of 167 patients with AS was included. Radiomic features were extracted from pelvis MRI after image preprocessing and feature engineering. Then, we performed unsupervised machine learning method to derive radiomics-based phenotypes. The validation and interpretation of derived phenotypes were conducted from the perspectives of clinical backgrounds and MRI characteristics. The association between derived phenotypes and radiographic outcomes was evaluated by multivariable analysis.Results1321 robust radiomic features were extracted and four biologically distinct phenotypes were derived. According to patient clinical backgrounds, phenotype I (38, 22.8%) and II (34, 20.4%) were labelled as high-risk while phenotype III (24, 14.4%) and IV (71, 42.5%) were at low risk for hip involvement. Consistently, the high-risk phenotypes were associated with higher prevalence of MRI-detected lesion than the low-risk. Moreover, phenotype I had significant acute inflammation signs than phenotype II, while phenotype IV was enthesitis-predominant. Importantly, the derived phenotypes were highly predictive of radiographic outcomes of patients, as the high-risk phenotypes were 3 times more likely to have radiological hip lesion than the low-risk [27 (58.7%) vs 16 (28.6%); adjusted odds ratio (OR) 2.95 (95% CI 1.10, 7.92)].ConclusionWe confirmed for the first time, the clinical actionability of profiling hip involvement in AS by radiomics method. Four distinct phenotypes of hip involvement in AS were identified and importantly, the high-risk phenotypes could predict structural damage of hip involvement in AS.

Objective Cognitive impairment in the elderly is a serious public health problem. However, the effect of the number of pregnancies and births in the early years of life on cognitive function in postmenopausal women remains controversial. This study aims to investigate the relationship between these two factors. Methods We used the National Health and Nutrition Examination Survey 2011-2014 data on women aged >= 60 years. This study included sociodemographic data, history of estrogen use, and contraceptive use as confounding variables. The combined scores of the Consortium to Establish a Registry for Alzheimer's Disease Word Learning (CERAD-WL), delayed word recall (CERAD-DR), the Animal Fluency test (AF), and the Digit Symbol Substitution Test (DSST) were used to assess the cognitive performance of participants. Hierarchical multiple regression analysis explored the relationship between the number of pregnancies and births and cognitive function. Results The study screened 1,259 postmenopausal women and found that 24.3% had low cognitive performance. The study found a significant increase in low cognitive performance among older adults, Mexican Americans, those with a lower education level and poverty-income ratio, those who were widowed, and those with diabetes and hypertension (P < 0.001). In the multiple regression analysis, the number of pregnancies remained a significant determinant of cognitive performance (B = -0.188, P < 0.001). Conclusions The number of pregnancies was associated with cognitive performance in a population of postmenopausal women in the United States. A lower number of pregnancies is associated with better cognitive performance.

IntroductionSymptoms during the onset of major depressive disorder [MDD] and bipolar disorder type II [BD-II] are similar. The difference of hippocampus subregion could be a biological marker to distinguish MDD from BD-II.MethodsWe recruited 61 drug-naïve patients with a first-episode MDD and BD-II episode and 30 healthy controls (HC) to participate in a magnetic resonance imaging [MRI] study. We built a general linear model (one-way analysis of covariance) with 22 hippocampal subfields and two total hippocampal volumes as dependent variables, and the diagnosis of MDD, BD-II, and HC as independent variables. We performed pair-wise comparisons of hippocampal subfield volumes between MDD and HC, BD-II and MDD, BD-II and HC with post hoc for primary analysis.ResultsWe identified three regions that differed significantly in size between patients and controls. The left hippocampal fissure, the hippocampal–amygdaloid transition area (HATA), and the right subiculum body were all significantly larger in patients with MDD compared with the HC. In the onset of first-episode of MDD, the hippocampal volume increased significantly, especially on the left side comparing to HC. However, we found differences between MDD and BD-II were not statistically significant. The volume of the left HATA and right subiculum body in BD-II was larger.ConclusionsThe sample size of this study is relatively small, as it is a cross-sectional comparative study. In both MDD and BD-II groups, the volume of more left subregions appeared to increase. The left subregions were severely injured in the development of depressive disorder.

The study aimed to investigate the association between long-term sedentary behavior (LTSB) and depressive symptoms within a representative sample of the U.S. adult population. Data from NHANES 2017–2018 were used, encompassing information on demographics, depressive symptoms, physical activity (PA), and LTSB. Depressive symptoms were identified using the Patient Health Questionnaire (PHQ-9), with “depressive symptoms” defined as a PHQ-9 score of ≥ 5, and “moderate to severe depressive symptoms (MSDS)” defined as a PHQ-9 score of ≥ 10. PA and LTSB were assessed through the Global Physical Activity Questionnaire, where LTSB was interpreted as sedentary time ≥ 600 min. Restricted Cubic Spline (RCS) curves were utilized to observe potential nonlinear relationships. Binary Logistic regressions were conducted to analyze the associations. A total of 4728 participants (mean age 51.00 ± 17.49 years, 2310 males and 2418 females) were included in the study. Among these individuals, 1194 (25.25%) displayed depressive symptoms, with 417 (8.82%) exhibiting MSDS. RCS curves displayed increased risk of depressive symptoms with prolonged sedentary duration. Logistic regression models indicated significant associations between LTSB and depressive symptoms (OR 1.398, 95% CI 1.098–1.780), and LTSB and MSDS (OR 1.567, 95% CI 1.125–2.183), after adjusting for covariates. These findings suggest that LTSB may act as a potential risk factor for both depressive symptoms and MSDS in the studied population.

The purpose of this study was to evaluate the association between recent tobacco smoking, household secondhand smoke exposure, confined space secondhand smoke exposure and depressive symptoms in young adults after adjustments for each other. Data from NHANES 2013–2018 were extracted. A total of 4129 young adults age 18–35 years (mean age 26.11 ± 5.39 years, 2021 males and 2108 females) were included. Depressive symptoms were screened by PHQ-9. Recent tobacco smoking was assessed through question “smoked tobacco in the last 5 days?”. Household secondhand smoke exposure was assessed through question “living with a smoker who smoked inside the house?”. Confined space secondhand smoke exposure was assessed by SSEQ. Binary logistic regression models were performed to analyze the associations. Significant association were observed in recent tobacco smoking (OR = 1.593, 95% CI 1.318–1.926) and confined space secondhand smoke exposure (OR = 1.399, 95% CI 1.185–1.651), but not in household secondhand smoke exposure (P = 0.108). Among the different settings of confined space secondhand smoke exposure, restaurant (OR = 1.732, 95% CI 1.120–2.678) and in-car (OR = 1.350, 95% CI 1.102–1.652) exposure were significantly associated with depressive symptom after after fully adjustments.

Background and aimsHuman studies about short-chain fatty acids (SCFAs), the gut microbiome, and Type 2 diabetes (T2DM) are limited. Here we explored the association between SCFAs and T2DM and the effects of gut microbial diversity on glucose status in rural populations.Methods and resultsWe performed a cross-sectional study from the Henan Rural Cohort and collected stool samples. Gut microbiota composition and faecal SCFA concentrations were measured by 16S rRNA and GC-MS. The population was divided based on the tertiles of SCFAs, and logistic regression models assessed the relationship between SCFAs and T2DM. Generalized linear models tested the interactions between SCFAs and gut microbial diversity on glucose indicators (glucose, HbAlc and insulin). Compared to the lowest tertile of total SCFA, acetate and butyrate, the highest tertile exhibited lower T2DM prevalence, with ORs and 95% CIs of 0.291 (0.085-0.991), 0.160 (0.044-0.574) and 0.171 (0.047-0.620), respectively. Restricted cubic spline demonstrated an approximately inverse S-shaped association. We also noted interactions of the ACE index with the highest tertile of valerate on glucose levels (P-interaction = 0.022) and the Shannon index with the middle tertile of butyrate on insulin levels (P-interaction = 0.034). Genus Prevotella_9 and Odoribacter were inversely correlated with T2DM, and the genus Blautia was positively associated with T2DM. These bacteria are common SCFA-producing members.ConclusionsInverse S-shaped associations between SCFAs (total SCFA, acetate, and butyrate) and T2DM were observed. Valerate and butyrate modify glucose status with increasing gut microbial diversity.

Introduction After decades of the one-child policy, China changed its rules to allow two children in 2016, which altered family dynamics. Few studies have examined the emotional problems and the family environment of multi-child adolescents. This study aims to explore the role of only-child status in the impact of childhood trauma and parental rearing style on depressive symptoms of adolescents in Shanghai, China. Methods A cross-sectional study was conducted on 4,576 adolescents (M = 13.42 years, SD = 1.21) from seven middle schools in Shanghai, China. Childhood Trauma Questionnaire-Short Form, the Short Egna Minnen Beträffande Uppfostran, and Children’s Depression Inventory were used to evaluate childhood trauma, perceived parental rearing style, and depressive symptoms of adolescents, respectively. Results Results showed that girls and non-only children reported more depressive symptoms, while boys and non-only children perceived more childhood trauma and negative rearing styles. Emotional abuse, emotional neglect, and father’s emotional warmth significantly predicted depressive symptoms in both only children and non-only children. Father’s rejection and mother’s overprotection were related to adolescents’ depressive symptoms in only-child families, but not non-only child families. Discussion Therefore, depressive symptoms, childhood trauma, and perceived negative rearing styles were more prevalent among adolescents in non-only child families, while negative rearing styles were especially associated with depressive symptoms in only children. These findings suggest that parents pay attention to their impacts on only children and give more emotional care to non-only children.