Independent and interaction effects of prenatal exposure to high AQI and extreme Humidex on the risk of preterm birth: A large sample population study in northern China.

The combined effects of air pollution and extreme temperature on PTB remain unclear. To evaluate the independent effect and interaction effect of prenatal extreme exposure to air quality index (AQI) and Humidex, on PTB. Based on the National Health Care Data Platform of Shandong University, women who gave birth in 2019-2020 were selected for the study. First, the independent effects of AQI and Humidex on PTB were assessed by logistic regression model. Subsequently, the interaction effects of AQI and Humidex on PTB were estimated separately by calculation of the relative excess risk of interaction (RERI). A total of 34365 pregnant women were included and 1975 subjects were diagnosed with PTB. We observed a significant increase in the odds of PTB associated with maternal high AQI exposure, with an OR of 1.70 (95% CI: 1.59, 1.81). Similarly, extreme exposure to Humidex also demonstrated an elevated PTB odds, with a low Humidex OR of 2.48 (95% CI: 2.23, 2.76) and a high Humidex OR of 1.48 (95% CI: 1.31, 1.67). Finally, we observed an interaction between high AQI and extreme Humidex during the 1st trimester. Interaction effects were noted between high AQI and low Humidex throughout the entire trimester and the 2nd trimester. This study suggests that prenatal exposure to high AQI and extreme Humidex could increase the odds of PTB, with effects exhibiting the sensitivity window and a cumulative trend. Additionally, there is an interaction between AQI and Humidex.

Prioritizing sustainable development goals in China based on a comprehensive assessment accounting for indicator interlinkages.

Prioritizing areas and targets, coordinated with development gaps, is necessary to achieve the sustainable development goals (SDGs) in the face of resource limitations resulting from coronavirus disease 2019 (COVID-19). The SDG interlinkages further exacerbate the difficulty inherent in addressing these goals. However, previous studies failed to consider the indicator interlinkages in the process of aggregate performance assessments and thus cannot identify priorities based on indicator interlinkages and development gaps. This study integrated network analysis and the technique for order of preference by similarity to ideal solution (TOPSIS) method to convert indicator interlinkages into indicator weights and then assessed the aggregate performance of the SDGs. Subsequently, the prioritized provinces and indicators were identified at the subnational level of China based on the aggregate performance of the SDGs, SDG growth rate and indicator interlinkages. The per capita net income of rural residents (2.3.2), the proportion of people living below 50% of the median income (10.2.1), and the under-five mortality rate (3.2.1) were the most contributing indicators to the aggregate performance of the SDGs, while the common challenges dealt with SDG 16, SDG 6, SDG 7 and SDG 12. Moreover, accelerating the development of western provinces would make it possible to overcome the traditional imbalance status, while resource-driven provinces should be paid special attention due to their poor aggregate performance of the SDGs and their lower growth rate. Thus, a coordinating strategy is highly recommended for allocating resources to the priority targets and finally achieving the SDGs.

Postoperative prognostic nomogram for adult grade II/III astrocytoma in the Chinese Han population.

Background: Prognostic models of glioma have been the focus of many studies. However, most of them are based on Western populations. Additionally, because of the complexity of healthcare data in China, it is important to select a suitable model based on existing clinical data. This study aimed to develop and independently validate a nomogram for predicting the overall survival (OS) with newly diagnosed grade II/III astrocytoma after surgery. Methods: Data of 472 patients with astrocytoma (grades II-III) were collected from Qilu Hospital as training cohort while data of 250 participants from Linyi People's Hospital were collected as validation cohort. Cox proportional hazards model was used to construct the nomogram and individually predicted 1-, 3-, and 5-year survival probabilities. Calibration ability, and discrimination ability were analyzed in both training and validation cohort. Results: Overall survival was negatively associated with histopathology, age, subtotal resection, multiple tumors, lower KPS and midline tumors. Internal validation and external validation showed good discrimination (The C-index for 1-, 3-, and 5-year survival were 0.791, 0.748, 0.733 in internal validation and 0.754, 0.735, 0.730 in external validation, respectively). The calibration curves showed good agreement between the predicted and actual 1-, 3-, and 5-year OS rates. Conclusion: This is the first nomogram study that integrates common clinicopathological factors to provide an individual probabilistic prognosis prediction for Chinese Han patients with astrocytoma (grades II-III). This model can serve as an easy-to-use tool to advise patients and establish optimized surveillance approaches after surgery. Supplementary Information: The online version contains supplementary material available at 10.1007/s13755-023-00223-0.

Impact of Isolation measures on pregnancy outcome during the COVID-19 pandemic.

This study aims to explore the impact of isolation measures implemented during the COVID-19 pandemic on childbirth outcomes in pregnant women. The design was a retrospective cohort study. The pregnant women during the outbreak lockdown and isolation from February 1 to April 30, 2020, were defined as the exposed population, and the pregnant women in the same time frame in 2019 as the non-exposed population. All data for the study were obtained from the National Health Care Data Platform of Shandong University. Generalized linear regression models were used to analyze the differences in pregnancy outcomes between the two study groups. A total of 34,698 pregnant women from Shandong Province, China in the data platform met the criteria and were included in the study. The proportions were 11.53% and 8.93% for macrosomia in the exposed and the non-exposed groups and were 3.47% and 4.37% for low birth weight infants, respectively, which were significantly different. They were 22.55% and 25.94% attributed to average exposed effect for macrosomia and low birth weight infants. Meanwhile, the mean weight and standard deviation of full-term infants in the exposure group were 3414.80 ± 507.43 g, which were significantly higher than in the non-exposed group (3347.22 ± 502.57 g, P < 0.001). The effect of exposure was significant in the third trimester. In conclusion, the isolation during the COVID-19 pandemic increases the birth weight of infants and the probability of macrosomia, regardless of which trimester in isolation a pregnant woman was, while the third trimester is the sensitive window of exposure. Our findings provide a basis for health care and policy development during pregnancy in COVID-19, due to COVID-19 still showing a pandemic trend around the world in 2022.

Changes and bioactivities on volatile organic compounds of endophytic fungi Neurospora dictyophora 3ZF-02 in different ages.

The endophytic fungus Neurospora dictyophora 3ZF-02 with a special aroma was isolated from the arils of Torreya grandis. Analysis of volatile organic compounds was done by gas chromatography-mass spectrometry. A total of 46 compounds were identified in the volatile organic compounds by 3ZF-02. In the growth phase, esters, acids, along with some alcohols and ketones were the main components. During the recession period, a large amount of benzene and naphthalene compounds appeared, accompanied by the production of amines. Oleic acid, methyl abietate, terpinen-4-ol were also found. They were the same ingredients in essential oil of Torreya. The antioxidant activity and antifungal activity of all extracts were also evaluated. When cultured for 10 days, it exhibited the most significant antioxidant activity with IC50 of 1.44 and 0.95 g/L against diphenyl picryl hydrazinyl and hydroxyl radicals, respectively. In addition, the extracts cultured for 10 days exhibited the most significant antifungal activity against Candida albicans with minimum inhibitory concentration 1.56 mg/ml.

Quantifying substantial carcinogenesis of genetic and environmental factors from measurement error in the number of stem cell divisions.

BACKGROUND: The relative contributions of genetic and environmental factors versus unavoidable stochastic risk factors to the variation in cancer risk among tissues have become a widely-discussed topic. Some claim that the stochastic effects of DNA replication are mainly responsible, others believe that cancer risk is heavily affected by environmental and hereditary factors. Some of these studies made evidence from the correlation analysis between the lifetime number of stem cell divisions within each tissue and tissue-specific lifetime cancer risk. However, they did not consider the measurement error in the estimated number of stem cell divisions, which is caused by the exposure to different levels of genetic and environmental factors. This will obscure the authentic contribution of environmental or inherited factors. METHODS: In this study, we proposed two distinct modeling strategies, which integrate the measurement error model with the prevailing model of carcinogenesis to quantitatively evaluate the contribution of hereditary and environmental factors to cancer development. Then, we applied the proposed strategies to cancer data from 423 registries in 68 different countries (global-wide), 125 registries across China (national-wide of China), and 139 counties in Shandong province (Shandong provincial, China), respectively. RESULTS: The results suggest that the contribution of genetic and environmental factors is at least 92% to the variation in cancer risk among 17 tissues. Moreover, mutations occurring in progenitor cells and differentiated cells are less likely to be accumulated enough for cancer to occur, and the carcinogenesis is more likely to originate from stem cells. Except for medulloblastoma, the contribution of genetic and environmental factors to the risk of other 16 organ-specific cancers are all more than 60%. CONCLUSIONS: This work provides additional evidence that genetic and environmental factors play leading roles in cancer development. Therefore, the identification of modifiable environmental and hereditary risk factors for each cancer is highly recommended, and primary prevention in early life-course should be the major focus of cancer prevention.

Investigation on bioactive metabolites produced by an endophytic fungus Trichoderma citrinoviride from the arils of Torreya grandis.

An endophytic fungus Trichoderma citrinoviride capable of producing active substances was isolated from the arils of Torreya grandis. Seven compounds were separated from the ethyl acetate extract of fermentation broth and mycelium by chromatography, respectively identified as trichomerol (1), bisorbicillinolide (2), sohirnone A (3), emodin (4), stigmasterol (5), ergosterol (6), daidzein (7). This study is the first to report of the isolation of the endophytic fungus T. citrinoviride from the arils of T. grandis with complete assignments of 1-7. Compound 1 and 2 exhibited significant antioxidant activity of diphenyl picryl hydrazinyl with IC50 38.92 and 3.91 µg/mL, respectively. Compound 1, 2, 4 and 7 significantly inhibited the growth of Staphylococcus aureus with MIC 0.78; 0.39; 0.20 and 0.20 mg/mL, respectively. Current study indicated the presence of endophytic fungus in the arils of Torreya grandis that could be responsible for the bioactive metabolite synthesis.

Profile and dynamics of infectious diseases: a population-based observational study using multi-source big data.

BACKGROUND: The current surveillance system only focuses on notifiable infectious diseases in China. The arrival of the big-data era provides us a chance to elaborate on the full spectrum of infectious diseases. METHODS: In this population-based observational study, we used multiple health-related data extracted from the Shandong Multi-Center Healthcare Big Data Platform from January 2013 to June 2017 to estimate the incidence density and describe the epidemiological characteristics and dynamics of various infectious diseases in a population of 3,987,573 individuals in Shandong province, China. RESULTS: In total, 106,289 cases of 130 infectious diseases were diagnosed among the population, with an incidence density (ID) of 694.86 per 100,000 person-years. Besides 73,801 cases of 35 notifiable infectious diseases, 32,488 cases of 95 non-notifiable infectious diseases were identified. The overall ID continuously increased from 364.81 per 100,000 person-years in 2013 to 1071.80 per 100,000 person-years in 2017 (χ2 test for trend, P < 0.0001). Urban areas had a significantly higher ID than rural areas, with a relative risk of 1.25 (95% CI 1.23-1.27). Adolescents aged 10-19 years had the highest ID of varicella, women aged 20-39 years had significantly higher IDs of syphilis and trichomoniasis, and people aged ≥ 60 years had significantly higher IDs of zoster and viral conjunctivitis (all P < 0.05). CONCLUSIONS: Infectious diseases remain a substantial public health problem, and non-notifiable diseases should not be neglected. Multi-source-based big data are beneficial to better understand the profile and dynamics of infectious diseases.

Relationships of sleep traits with prostate cancer risk: A prospective study of 213,999 UK Biobank participants.

BACKGROUND: The effect of sleep on the occurrence of prostate cancer (PCa) remains unclear. This study explored the influence of sleep traits on the incidence of PCa using a UK Biobank cohort study. METHODS: In this prospective cohort study, 213,999 individuals free of PCa at recruitment from UK Biobank were included. Missing data were imputed using multiple imputation by chained equations. Cox proportional hazards models were used to calculate the adjusted hazard ratios and 95% confidence intervals for PCa (6747 incident cases) across seven sleep traits (sleep duration, chronotype, insomnia, snoring, nap, difficulty to get up in the morning, and daytime sleepiness). In addition, we newly created a healthy sleep quality score according to sleep traits to assess the impact of the overall status of night and daytime sleep on PCa development. E values were used to assess unmeasured confounding. RESULTS: We identified 6747 incident cases, of which 344 died from PCa. Participants who usually suffered from insomnia had a higher risk of PCa (hazard ratio [HR]: 1.11; 95% confidence interval [CI]: 1.04-1.19, E value: 1.46). Finding it fairly easy to get up in the morning was also positively associated with PCa (HR: 1.09; 95% CI: 1.04-1.15, E value: 1.40). Usually having a nap was associated with a lower risk of PCa (HR: 0.91; 95% CI: 0.83-0.99, E value: 1.42). CONCLUSIONS: Fairly easy to get up in the morning and usually experiencing insomnia were associated with an increased incidence of PCa. Moreover, usually having a nap was associated with a lower risk of PCa. Therefore, sleep behaviors are modifiable risk factors that may have a potential impact on PCa risk.

Effective Macrosomia Prediction Using Random Forest Algorithm.

(1) Background: Macrosomia is prevalent in China and worldwide. The current method of predicting macrosomia is ultrasonography. We aimed to develop new predictive models for recognizing macrosomia using a random forest model to improve the sensitivity and specificity of macrosomia prediction; (2) Methods: Based on the Shandong Multi-Center Healthcare Big Data Platform, we collected the prenatal examination and delivery data from June 2017 to May 2018 in Jinan, including the macrosomia and normal-weight newborns. We constructed a random forest model and a logistic regression model for predicting macrosomia. We compared the validity and predictive value of these two methods and the traditional method; (3) Results: 405 macrosomia cases and 3855 normal-weight newborns fit the selection criteria and 405 pairs of macrosomia and control cases were brought into the random forest model and logistic regression model. On the basis of the average decrease of the Gini coefficient, the order of influencing factors was: interspinal diameter, transverse outlet, intercristal diameter, sacral external diameter, pre-pregnancy body mass index, age, the number of pregnancies, and the parity. The sensitivity, specificity, and area under curve were 91.7%, 91.7%, and 95.3% for the random forest model, and 56.2%, 82.6%, and 72.0% for logistic regression model, respectively; the sensitivity and specificity were 29.6% and 97.5% for the ultrasound; (4) Conclusions: A random forest model based on the maternal information can be used to predict macrosomia accurately during pregnancy, which provides a scientific basis for developing rapid screening and diagnosis tools for macrosomia.

High Prevalence of Asymptomatic Intracranial Atherosclerosis in Elder Women With Tubal Ligation: Result From a Community-Based Study in Shandong, China.

Background: In addition to traditional cardiovascular risk factors, gender-specific factors may also contribute to intracranial atherosclerosis. This study aimed to comprehensively investigate the association between asymptomatic intracranial atherosclerosis (aICAS) and menstrual or reproductive history (MRH), namely, menstruation, pregnancy, childbirth, menopause, and contraception. Methods: Participants in this study were selected from the Kongcun town aICAS study. MRH was collected through structured case report forms, in which menarche age, menstrual regularity, dysmenorrhea, number of pregnancies, number of childbirths, age of first pregnancy, breastfeeding, menopause, menopause age, and contraceptive methods were all involved. All characteristics were compared by chi-squared and nonparametric tests as applicable. Logistic regression model and sensitivity analysis were used to analyze the association between aICAS and MRH. Results: A total of 1,052 female participants were involved in this study, of which 5.7% had moderate to severe aICAS. Tubal ligation was significantly associated with aICAS in univariate analysis [crude odds ratio (OR), 2.85; 95% CI, 1.22-6.62; P = 0.015]. This association was still significant among female participants over 60 years old after multivariate adjustment (adjusted OR, 4.36; 95% CI, 1.55-12.24; P = 0.005). Sensitivity analysis showed a similar result (adjusted OR, 3.76; 95% CI, 1.24-11.41; P = 0.020). Menopause lost significant association with aICAS after multivariate adjustment (adjusted OR, 1.68; 95% CI, 0.66-4.24; P = 0.275). No other MRH factors were found to be associated with aICAS. Conclusion: Tubal ligation may be associated with a higher prevalence of aICAS in Chinese elderly women. This provides a new perspective to study the epidemiological characteristics of ICAS.

The TARGET Nurses' health cohort study protocol: Towards a revolution in getting nurses' health ticked.

AIM: To evaluate the health status of nurses in China and explore the impact of work-related stress, work environment and lifestyle factors on their health outcomes. DESIGN: The Chinese Nurses' Health Study is a multicentred, prospective cohort study. METHODS: We plan to recruit approximately 80,000 registered nurses aged between 18 and 65 years. Eligible nurses will be introduced to complete a series of web-based questionnaires after obtaining their informed consent. Follow-up questionnaires will be completed at 2-year interval to continuously track subsequent exposures. Health-related indicators will be obtained through self-reporting by nurses and the provincial and national registry platforms such as National Central Cancer Registry. The funding was approved in July 2020 and Research Ethics Committee approval was granted in February 2021. DISCUSSION: The study is the first multicentred prospective cohort study that aims to assess the impact of work-related stress, work environment and lifestyle factors on the health of Chinese nurses. The results of the Chinese Nurses' Health Cohort Study will potentially draw a picture of the current situation of general health and well-being among nurses in China and their health risks. This will be critical in recommending locally tailored strategic preventive measures and policies to reduce health and well-being threats for nurses and potentially general public, thereby promoting the quality of healthcare in China and globally. IMPACT: This study will help to understand the health status and working environment characteristics of Chinese nurses, and provide valuable epidemiological evidence for improving working environment and promoting well-being. The results of this study are potentially of great significance for formulating targeted nursing strategies to promote the nurses' health, nursing quality and patient safety in China and even around the world. CLINICAL TRIAL REGISTRATION NUMBER AND NAME OF TRIAL REGISTER: ChiCTR.org (ID:ChiCTR2100043202), The Nurses' Health Cohort Study of Shandong.

Machine Learning Applications in Drug Repurposing.

The coronavirus disease (COVID-19) has led to an rush to repurpose existing drugs, although the underlying evidence base is of variable quality. Drug repurposing is a technique by taking advantage of existing known drugs or drug combinations to be explored in an unexpected medical scenario. Drug repurposing, hence, plays a vital role in accelerating the pre-clinical process of designing novel drugs by saving time and cost compared to the traditional de novo drug discovery processes. Since drug repurposing depends on massive observed data from existing drugs and diseases, the tremendous growth of publicly available large-scale machine learning methods supplies the state-of-the-art application of data science to signaling disease, medicine, therapeutics, and identifying targets with the least error. In this article, we introduce guidelines on strategies and options of utilizing machine learning approaches for accelerating drug repurposing. We discuss how to employ machine learning methods in studying precision medicine, and as an instance, how machine learning approaches can accelerate COVID-19 drug repurposing by developing Chinese traditional medicine therapy. This article provides a strong reasonableness for employing machine learning methods for drug repurposing, including during fighting for COVID-19 pandemic.

Predictors of Shift Work Sleep Disorder Among Nurses During the COVID-19 Pandemic: A Multicenter Cross-Sectional Study.

Background: Nurses have a high incidence of shift work sleep disorder, which places their health and patient safety in danger. Thus, exploring the factors associated with shift work sleep disorder in nurses is of great significance in improving their sleep health, nursing personnel staffing, and scheduling during the COVID-19 pandemic. Objectives: The purpose of this study was to investigate the incidence of shift work sleep disorder during the COVID-19 pandemic and explore the factors associated with shift work sleep disorder in Chinese nurses. Methods: This was a multicenter cross-sectional study using an online survey. Stratified cluster sampling was used to include 4,275 nurses from 14 hospitals in Shandong, China from December 2020 to June 2021. Stepwise multivariate logistic regression analysis and random forest were used to identify the factors associated with shift work sleep disorder. Results: The prevalence of shift work sleep disorder in the sampled shift nurses was 48.5% during the COVID-19 pandemic. Physical fatigue, psychological stress, shift work more than 6 months per year, busyness during night shift, working more than 40 h per week, working more than four night shifts per month, sleeping more than 8 h before night shift, using sleep medication, irregular meals, and high-intensity physical activity were associated with increased odds of shift work sleep disorder. Good social support, good work-family balance, napping two or three times per week, resting more than one day after shifts, intervals of 8 days or more between shifts, and taking turns to rest during the night shift were associated with decreased odds of shift work sleep disorder. Conclusions: Shift work sleep disorder may be associated with scheduling strategies and personal behavior during the COVID-19 pandemic. To reduce the incidence of shift work sleep disorders in nurses, nursing managers should increase night shift staffing, extend rest days after shift, increase night shift spacing, and reduce overtime, and nurses need to seek more family and social support and control their sleep schedules and diet.

Association of triglyceride-glucose index and high-sensitivity C-reactive protein with asymptomatic intracranial arterial stenosis: A cross-sectional study.

BACKGROUND AND AIMS: Triglyceride-glucose index (TyG) and high-sensitivity C-reactive protein (hsCRP) have been shown to play important roles in the pathophysiological mechanisms of atherogenesis. However, the cumulative value of TyG and hsCRP in identifying asymptomatic intracranial arterial stenosis (aICAS), as well as its severity and numerical burden, is uncertain. This study seeks to fill this knowledge gap. METHODS AND RESULTS: This study included 1938 participants aged ≥40 years who were free of stroke or transient ischemic attack. All participants were classified into four groups based on the participants' TyG and hsCRP levels, including low-TyG and low-hsCRP, low-TyG and high-hsCRP, high-TyG and low-hsCRP, and high-TyG and high-hsCRP groups. The presence of aICAS was screened via transcranial Doppler ultrasound and confirmed by magnetic resonance angiography. The TyG was calculated as ln [fasting triglyceride (mg/dL) × fasting glucose (mg/dL)/2]. We used multinomial logistic regression analysis to investigate the cumulative value of TyG and hsCRP on identifying the severity of aICAS or its numerical burden. After adjustment for conventional confounders, isolated high-hsCRP, isolated high-TyG, and high-TyG combined with high-hsCRP were independently associated with moderate-to-severe aICAS. Compared with the low-TyG and low-hsCRP group, participants with high-TyG and high-hsCRP had a 2.6 times higher odds ratio (OR) of having a single moderate-to-severe aICAS and a 3.3 times higher OR of having multiple moderate-to-severe aICASs. CONCLUSION: The cumulative value of TyG and hsCRP may better identify moderate-to-severe aICAS as well as its numerical burden.

Association between homocysteine and white matter hyperintensities in rural-dwelling Chinese people with asymptomatic intracranial arterial stenosis: A population-based study.

PURPOSE: Although homocysteine (Hcy) has been proven to be associated with the incidence of white matter hyperintensities (WMH) in patients with stroke, this association remains unclear in participants with asymptomatic intracranial arterial stenosis (aICAS). This study aimed to investigate the association of Hcy with WMH in participants with aICAS. MATERIALS AND METHODS: This was a cross-sectional study based on the Kongcun Town Study. Participants diagnosed with aICAS by magnetic resonance angiography in the Kongcun Town Study were enrolled in this study. Data on demographics, lifestyle, medical histories, and Hcy levels were collected via interviews, clinical examinations, and laboratory tests. The volume of WMH was calculated using the lesion segmentation tool system for the Statistical Parametric Mapping package based on magnetic resonance imaging. The association between Hcy and WMH volume was analyzed using linear and logistic regression analyses. RESULTS: A total of 137 aICAS participants were enrolled in the present study. Hcy was associated with the incidence of severe WMH (4th quartile, ≥4.20 ml) after adjustment for certain covariates [Hcy as a continuous variable, odds ratio (95% confidence interval) (OR (95% CI)): 1.09 (1.00, 1.19), p = .047; as a categorical variable (Hcy ≥15 µmol/L), OR (95% CI): 3.74 (1.37, 10.19), p = .010)]. After stratification according to the degree of aICAS, this relationship remained significant only in the moderate-to-severe stenosis group (stenosis ≥50%). (Hcy as continuous variable, OR (95% CI): 1.14 (1.02, 1.27), p = .025; as a categorical variable (Hcy ≥15 µmol/L), OR (95% CI): 5.59 (1.40, 15.25), p = .015). CONCLUSION: Serum Hcy concentration may be positively associated with the volume of WMH in rural-dwelling Chinese people with moderate-to-severe (stenosis ≥50%) aICAS.

Association Between Metabolic Syndrome and Asymptomatic Cerebral Arterial Stenosis: A Cross-Sectional Study in Shandong, China.

Metabolic syndrome (MetS) can worsen cerebral arterial atherosclerosis stenosis in patients with stroke; however, its effect on patients without stroke remains ambiguous. This study explored the association of MetS and its individual components with asymptomatic intracranial arterial stenosis (aICAS) and asymptomatic extracranial arterial stenosis (aECAS) among older Chinese adults. A total of 1988 participants from the Kongcun Town study aged ≥40 years and without a history of stroke were enrolled. The baseline data were obtained via face-to-face interviews. MetS was defined according to International Diabetes Federation criteria. Detection of aICAS was conducted using transcranial Doppler ultrasound, followed by diagnosis via magnetic resonance angiography. The evaluation of aECAS was performed using bilateral carotid ultrasonography. The aICAS and aECAS groups were 1:1 matched separately to the non-stenosis group by age and sex. The association between MetS and aICAS or aECAS was analyzed using multivariate logistic regression. Among the 1988 participants, 909 were diagnosed with MetS. The prevalence of MetS was higher in the aICAS group than in the non-stenosis group (P <0.001), but did not differ significantly between the aECAS and non-stenosis groups. The prevalence of aICAS increased with the number of MetS components from 3.4% in the ≤ 1 component group to 12.7% in the ≥4 components group (P for trend <0.001). After adjusting for confounding factors, MetS components associated with aICAS included central obesity, elevated triglyceride levels, and elevated blood pressure. None of the MetS components was associated with aECAS. MetS was positively associated with aICAS, but not with aECAS. Further, different components play different roles in the pathological process leading to aICAS.

Association between asymptomatic intracranial arterial stenosis and insulin resistance or diabetes mellitus: a cross-sectional study in rural Shandong, China.

INTRODUCTION: Recent studies have shown that insulin resistance (IR) is correlated to atherosclerosis development. However, few studies have investigated the association between IR and asymptomatic intracranial arterial stenosis (aICAS). RESEARCH DESIGN AND METHODS: This cross-sectional study enrolled 2007 rural residents in China who were aged ≥40 years without a clinical history of stroke and transient ischaemic attack. We used transcranial Doppler ultrasonography in combination with magnetic resonance angiography to diagnose aICAS (stenosis ≥50%). IR was defined as a homeostasis model assessment of insulin resistance ≥3.0 based on the 75th percentile for all the participants. Multivariate logistic regression models were employed to assess the relationship of diabetic parameters with aICAS in all participants, as well as with aICAS in non-diabetic participants, and further stratified by sex. RESULTS: After adjusting for age, gender, smoking habit, drinking habit, low-density lipoprotein cholesterol, raised blood pressure, triglycerides, high-density lipoprotein cholesterol and waist circumference, diabetes mellitus (DM) (OR=2.09, 95% CI 1.31 to 3.32), fasting plasma glucose (FPG) (OR=1.34, 95% CI 1.14 to 1.57), and IR (OR=1.75, 95% CI 1.11 to 2.75) were associated with aICAS in the total study population; however, these relationships remained significant only in men after the analyses were stratified by sex (DM: OR=3.40, 95% CI 1.62 to 7.13; FPG: OR=1.64, 95% CI 1.26 to 2.13; IR: OR=3.04, 95% CI 1.44 to 6.42). When further excluding the diabetic participants from the total study population, positive associations between IR and aICAS were similarly observed only in men (OR=4.65, 95% CI 1.69 to 12.82). CONCLUSIONS: IR might predict the prevalence of aICAS independently of major cardiovascular risk factors and metabolic syndrome components among men living in rural China.

Epidemic and control of COVID-19 in Niger: quantitative analyses in a least developed country.

BACKGROUND: The COVID-19 pandemic is challenging the public health response system worldwide, especially in poverty-stricken, war-torn, and least developed countries (LDCs). METHODS: We characterized the epidemiological features and spread dynamics of COVID-19 in Niger, quantified the effective reproduction number (Rt ), evaluated the impact of public health control measures, and estimated the disease burden. RESULTS: As of 4 July 2020, COVID-19 has affected 29 communes of Niger with 1093 confirmed cases, among whom 741 (67.8%) were males. Of them 89 cases died, resulting in a case fatality rate (CFR) of 8.1%. Both attack rates and CFRs were increased with age (P < 0.0001). Health care workers accounted for 12.8% cases. Among the reported cases, 39.3% were isolated and treated at home, and 42.3% were asymptomatic. 74.6% cases were clustered in Niamey, the capital of Niger. The Rt fluctuated in correlation to control measures at different outbreak stages. After the authorities initiated the national response and implemented the strictest control measures, Rt quickly dropped to below the epidemic threshold (<1), and maintained low level afterward. The national disability-adjusted life years attributable to COVID-19 was 1267.38 years in total, of which years of life lost accounted for over 99.1%. CONCLUSIONS: Classic public health control measures such as prohibition of public gatherings, travelling ban, contact tracing, and isolation and quarantine at home, are proved to be effective to contain the outbreak in Niger, and provide guidance for controlling the ongoing COVID-19 pandemic in LDCs.

Impacts of transportation and meteorological factors on the transmission of COVID-19.

The ongoing pandemic of 2019 novel coronavirus disease (COVID-19) is challenging global public health response system. We aim to identify the risk factors for the transmission of COVID-19 using data on mainland China. We estimated attack rate (AR) at county level. Logistic regression was used to explore the role of transportation in the nationwide spread. Generalized additive model and stratified linear mixed-effects model were developed to identify the effects of multiple meteorological factors on local transmission. The ARs in affected counties ranged from 0.6 to 9750.4 per million persons, with a median of 8.8. The counties being intersected by railways, freeways, national highways or having airports had significantly higher risk for COVID-19 with adjusted odds ratios (ORs) of 1.40 (p = 0.001), 2.07 (p < 0.001), 1.31 (p = 0.04), and 1.70 (p < 0.001), respectively. The higher AR of COVID-19 was significantly associated with lower average temperature, moderate cumulative precipitation and higher wind speed. Significant pairwise interactions were found among above three meteorological factors with higher risk of COVID-19 under low temperature and moderate precipitation. Warm areas can also be in higher risk of the disease with the increasing wind speed. In conclusion, transportation and meteorological factors may play important roles in the transmission of COVID-19 in mainland China, and could be integrated in consideration by public health alarm systems to better prevent the disease.