bluuebunny/crossref_metadata_2025_split huggingface dataset:
Associations between mental health competence and indicators of physical health and cognitive development in eleven year olds: findings from the UK Millennium Cohort Study
Authors: Hope Steven , Rougeaux Emeline , Deighton Jessica , Law Catherine , Pearce Anna 
Published: November 2019

Abstract

Background
Positive mental health may support healthy development in childhood, although few studies have investigated this at a population level. We aimed to construct a measure of mental health competence (MHC), a skills-based assessment of positive mental health, using existing survey items in a representative sample of UK children, and to investigate its overlap with mental health difficulties (MHD), socio-demographic patterning, and relationships with physical health and cognitive development.

Methods
We analysed the UK Millennium Cohort Study (MCS) when children were aged 11 years. Maternal (n = 12,082) and teacher (n = 6739) reports of prosocial behaviours (PS) and learning skills (LS) were entered into latent class models to create MHC measures. Using descriptive statistics, we examined relationships between MHC and MHD, and the socio-demographic patterning of MHC. Associations between MHC and physical health and cognitive development were examined with relative risk ratios [RRR] (from multinomial models): BMI status (healthy weight, overweight, obesity); unintentional injuries since age 7 (none, 1, 2+); asthma symptoms (none, 1, 2+); and tertiles of test scores for verbal ability, spatial working memory and risk-taking. Models were adjusted for potential confounding.

Results
Four MHC classes were identified [percentages for maternal and teacher reports, respectively]: high MHC (high PS, high LS) [37%; 39%], high-moderate MHC (high PS, moderate LS) [36%; 26%]; moderate MHC (moderate PS, moderate LS) [19%; 19%]; low MHC (moderate PS, low LS) [8%; 16%]. Higher MHC was less common in socially disadvantaged children. While MHC and MHD were associated, there was sufficient separation to indicate that MHC captures more than the absence of MHD. Compared to children with high MHC, those in other MHC classes tended to have poorer physical health and cognitive development, particularly those with low MHC or high-moderate MHC. For example, children with maternal-report Low MHC were more likely to have experienced 2+ unintentional injuries (RRR: 1.5 [1.1–2.1]) and to have lower verbal ability scores (RRR: 2.5 [1.9–3.2]). Patterns of results were similar for maternal- and teacher-report MHC.

Conclusion
MHC is not simply the inverse of MHD, and high MHC is associated with better physical health and cognitive development. Findings suggest that interventions to improve MHC may support healthy development, although they require replication.
Tobacco use and associated risk factors in Burkina Faso: results from a population-based cross-sectional survey
Authors: Bonnechère Bruno , Cissé Kadari , Millogo Tiéba , Ouédraogo Gautier H. , Garanet Franck , Ouedraogo Mariam A. , Boyle Gabriela , Samadoulougou Sékou , Kouanda Seni , Kirakoya-Samadoulougou Fati 
Published: November 2019

Abstract

Background
Tobacco is a leading preventable cause of non-communicable diseases (NCDs). Studies characterizing the prevalence of tobacco use in low-income countries are lacking. This study describes the prevalence of tobacco use in Burkina Faso and its associated factors.

Methods
Data from the 2013 Burkina Faso World Health Organization (WHO) Stepwise approach to Surveillance (STEPS) were analyzed. The prevalence of any tobacco product use, cigarette smoking, and other tobacco use was calculated. Logistic regression analyses identified factors associated with tobacco use. Overall, 4691 people were included in this analysis.

Results
The prevalence of any tobacco use was 19.8% (95% CI: 18.4–21.2). Tobacco use was higher for men (29.2% [27.0–31.5]) than women (11.8% [10.3–13.4]). The prevalence of smoked tobacco was 11.3% (10.3–12.4), with a significantly higher prevalence among men (24.5% [22.1–27.0]) than women (0.1% [0.01–0.3]). The overall prevalence of other tobacco use was 8.9% (7.4–10.7), with lower values for men (5.6% [4.1–7.2]) compared to women (11.7% [9.4–14.1]). Tobacco smoking among men was significantly associated with an increased age and alcohol consumption. The analysis of risk factors for other tobacco use stratified by gender showed that age, education, residence, and alcohol consumption were significantly associated with consumption for women, and age and alcohol consumption for men.

Conclusion
Tobacco use is common in Burkina Faso. To effectively reduce tobacco use in Burkina Faso, a comprehensive tobacco control program should consider associated factors, such as gender, age, and alcohol consumption.
Socioeconomic inequalities in the prevalence of chronic diseases and preventive care among adults aged 45 and older in Shaanxi Province, China
Authors: Lai Sha , Shen Chi , Yang Xiaowei , Zhang Xiaolong , Xu Yongjian , Li Qian , Gao Jianmin , Zhou Zhongliang 
Published: November 2019

Abstract

Background
Monitoring inequalities in chronic disease prevalence and their preventive care can help build effective strategies to improve health equality. Using hypertension and diabetes as a model, this study measures and decomposes socioeconomic inequalities in their prevalence and preventive care among Chinese adults aged 45 years and older in Shaanxi Province, an underdeveloped western region of China.

Methods
Data of 27,728 respondents aged 45 years and older who participated in the fifth National Health Services Survey conducted in 2013 in Shaanxi Province were analyzed. The relative indexes of inequalities based on Poisson regressions were used to assess disparities in the prevalence of hypertension and diabetes and their preventive care between those with the lowest and the highest socioeconomic status, and the concentration index was used to measure the magnitude of the socioeconomic-related inequality across the entire socioeconomic spectrum. The contribution of each factor to the inequality was further estimated via the concentration index decomposition.

Results
Our results indicate a higher prevalence of hypertension and diabetes among the rich than the poor individuals aged 45 years and older in Shaanxi Province, China. Among individuals with hypertension or diabetes, significant inequalities favoring the rich were observed in the use of preventive care, i.e. in adequate use of medication and of blood pressure/blood glucose monitoring. Furthermore, economic status, educational level, employment status, and urban-rural areas were identified as the key socioeconomic indicators for monitoring the inequalities in the patient preventive care.

Conclusions
Our study suggests that the existence of clear inequities in the prevalence of chronic diseases and preventive care among adults aged 45 and older in Shaanxi Province, China. These inequalities in chronic diseases could be as much a cause as a consequence of socioeconomic inequalities.
Spine surgeon specialty differences in single-level percutaneous kyphoplasty
Authors: Hu Kejia , Liu Motao , Wang Amy J. , Zhao Gexin , Sun Yuhao , Yang Chaoqun , Zhang Yiwang , Hutter Matthew M. , Feng Dehong , Sun Bomin , Williams Ziv 
Published: November 2019

Abstract

Background
Percutaneous kyphoplasty (PKP) is a procedure performed by a spine surgeon who undergoes either orthopedic or neurosurgical training. The relationship between short-term adverse outcomes and spine specialty is presently unknown. To compare short-term adverse outcomes of single-level PKP when performed by neurosurgeons and orthopedic surgeons in order to develop more concretely preventive strategies for patients under consideration for single-level PKP.

Methods
We evaluated patients who underwent single-level PKP from 2012 to 2014 through the American College of Surgeons National Surgical Quality Improvement Program (ACS NSQIP). We used univariate analysis and multivariate logistic regression to assess the association between spine surgeon specialty and short-term adverse events, including postoperative complication and unplanned readmission, and to identify different independent risk predictors between two specialties.

Results
Of 2248 patients who underwent single-level PKP procedure, 1229 patients (54.7%) had their operations completed by a neurosurgeon. There were no significant differences in the development of the majority of postoperative complications and the occurrence of unplanned readmission between the neurosurgical cohort (NC) and the orthopedic cohort (OC). A difference in the postoperative blood transfusion rate (0.7% NS vs. 1.7% OC, P = 0.039) was noted and may due to the differences in comorbidities between patients. Multivariate regression analysis revealed different independent predictors of postoperative adverse events for the two spine specialties.

Conclusions
By comparing a large range of demographic feature, preoperative comorbidities, and intraoperative factors, we find that short-term adverse events in single-level PKP patients does not affect by spine surgeon specialty, except that the OC had higher postoperative blood transfusion rate. In addition, the different perioperative predictors of postoperative complications and unplanned readmissions were identified between the two specialties. These findings can lead to better evidence-based patient counseling and provide valuable information for medical evaluation and potentially devise methods to reduce patients’ risk.
“We are responsible for the violence, and prevention is up to us”: a qualitative study of perceived risk factors for gender-based violence among Ethiopian university students
Authors: Kaufman Michelle R. , Williams Ashlie M. , Grilo Graziele , Marea Christina X. , Fentaye Fasil Walelign , Gebretsadik Lakew Abebe , Yedenekal Shifera Asfaw 
Published: November 2019

Abstract

Background
There is a high prevalence of gender-based violence (GBV) victimization among young Ethiopian women, including in universities, where female enrollment is low but growing. Understanding factors contributing to GBV in this context and students’ perspectives on gender, relationships, and interpersonal violence is essential to creating effective interventions to prevent GBV and support female students’ rights and wellbeing.

Methods
In-depth interviews (IDIs) and focus group discussions (FGDs) were held with male and female students (male IDI n = 36, female IDI n = 34, male FGD n = 18, female FGD n = 19) and faculty and staff (FGD n = 19) at two Ethiopian universities. Audio recordings were transcribed and translated into English. Transcripts were coded thematically to identify key factors contributing to GBV and provide narratives of students’ experiences.

Results
GBV against female students was a salient issue, including narrative accounts of harassment, intimidation, and physical and sexual violence on the university campuses and the towns in which they are located. Reported risks for GBV included receiving academic support from male peers, exercising agency in relationship decision-making, having a negative self-concept, belief in stereotypical gender expectations, and engaging in transactional sex and/or substance use. While students recognized these risk factors, they also suggested GBV may be the result of females’ “improper” behavior, attire, use of males for personal gain, or personal failure to prevent violence.

Conclusions
GBV is a serious issue in these two Ethiopian universities, creating a tenuous learning environment for female students. Programs are needed to address areas of vulnerability and negative attitudes toward female students in order to decrease female victimization.
Isolation of bioactive compounds from Bergenia ciliata (haw.) Sternb rhizome and their antioxidant and anticholinesterase activities
Authors: Zafar Roheena , Ullah Habib , Zahoor Muhammad , Sadiq Abdul 
Published: November 2019

Abstract

Background
Bergenia ciliata is a medicinal plant used for the treatment of diarrhea, vomiting, fever, cough, diabetes, cancer, pulmonary disorders and wound healing.

Methods
In this study, Bergenia ciliata crude extract, subfractions, and isolated compounds were evaluated for their antioxidant and anticholinesterase potential. The free radical scavenging capacities of the extracts determined using DPPH and ABTS assays. The anticholinesterase potentials were determined using acetylcholine esterase and butyryl choline esterase enzymes. To determine the phytochemical composition, the extracts were subjected to HPLC analysis and silica gel column isolation. Based on HPLC fingerprinting results, the ethyl acetate fraction was found to have more bioactive compounds and was therefore subjected to silica gel column isolation. As a result, three compounds; pyrogallol, rutin, and morin were isolated in the pure state. The structures of the isolated compounds were elucidated using spectroscopic techniques like 1H-NMR, IR and UV-Visible.

Results
The crude extract showed maximum anticholinesterase (acetylcholinesterase = 90.22 ± 1.15% and butyrylcholinesterase = 88.22 ± 0.71%) and free radical scavenging (87.37 ± 2.45 and 83.50 ± 0.70% respectively against DPPH and ABTS radicals) potentials. The total phenolic contents (expressed as equivalent of gallic acid; mgGAE/g) were higher in ethyl acetate fraction (80.96 ± 1.74) followed by crude extract (70.65 ± 0.86) while the flavonoid contents (expressed as quercetin equivalent; mgQE/g) and were higher in crude extract (88.40 ± 1.12) followed by n-butanol fraction (60.10 ± 1.86). The isolated bioactive compounds pyrogallol, rutin, and morin were found active against ABTS and DPPH free radicals. Amongst them, pyrogallol was more active against both free radicals. Reasonable anticholinesterase activities were recorded for pyrogallol against selected enzymes.

Conclusion
The extracts and isolated compounds showed antioxidant and acetylcholinesterase inhibitory potentials. It was concluded that this plant could be helpful in the treatment of oxidative stress and neurological disorders if used in the form of extracts.
Characterization, evaluation of nutritional parameters of Radix isatidis protein and its antioxidant activity in D-galactose induced ageing mice
Authors: Xiao Ping , Huang Hongzhi , Li Xiang , Chen Jianwei , Duan Jin-ao 
Published: November 2019

Abstract

Background
Radix isatidis (Isatis indigotica Fort.) is an ancient medicinal herb, which has been applied to the prevention and treatment of influenza virus since ancient times. In recent years, the antioxidant activity of Radix isatidis has been widely concerned by researchers. Our previous studies have shown that Radix isatidis protein (RIP) has good antioxidant activity in vitro. In this study, the composition of the protein was characterized and its antioxidant activity in vivo was evaluated.

Methods
The model of oxidative damage in mice was established by subcutaneous injection of D-galactose for 7 weeks. Commercially available kits were used to determine the content of protein and several oxidation indexes in different tissues of mice. The tissue samples were stained with hematoxylin and eosin (H&E) and the pathological changes were observed by optical microscope. The molecular weight of RIP was analyzed by sodium dodecyl sulfate polyacrylamide gel electrophoresis (SDS-PAGE). The amino acid composition of RIP was determined by a non-derivative method developed by our research group.

Results
RIP significantly increased the activities of antioxidant enzymes such as SOD, CAT, GSH-Px and total antioxidant capability (TAOC) but decreased the MDA level in the serum, kidney and liver. H&E stained sections of liver and kidney revealed D-galactose could cause serious injury and RIP could substantially attenuate the injury. The analysis of SDS-PAGE showed that four bands with molecular weights of 19.2 kDa, 21.5 kDa, 24.8 kDa and 40.0 kDa were the main protein components of RIP.

Conclusions
The results suggested that RIP had excellent antioxidant activity, which could be explored as a health-care product to retard aging and a good source of protein nutrition for human consumption.
Complementary and alternative medicine use among infertile women attending infertility specialty clinics in South Korea: does perceived severity matter?
Authors: Hwang Jung Hye , Kim Yi Young , Im Hyea Bin , Han Dongwoon 
Published: November 2019

Abstract

Background
Complementary and alternative medicine (CAM) use among infertile women is popular in many countries, including Korea. Previous research has repeatedly found more than half of infertile women surveyed use CAM therapies for fertility enhancement and overall well-being. However, there is currently little evidence to support this practice, and this raises the question of infertile women’s experiences in the uptake of those modalities and sociodemographic and psychological factors associated with CAM use. Thus, this study aims to explore the perceptions and experiences of infertile women with regard to their use of CAM in Korea.

Methods
A cross-sectional study was conducted using data from 263 infertile women attending infertility specialty clinics in Seoul, Korea, in June 2012. The survey instrument included 47 questions on the use of CAM, demographic characteristics, health status, and infertility related factors such as duration and type of infertility, experience and satisfaction of conventional treatment, and self-perceived severity of infertility condition. Chi-square test and logistic regression were used for data analysis.

Results
Among 286 respondents (response rate, 95.3%), a total of 263 women were included in the final analysis. 63.5% of respondents used one or more types of CAM modalities during infertility treatment. The utilization of CAM was associated with employment status, duration of infertility treatment, and self-perceived severity of the disease. The most commonly used CAM modalities were multivitamin and herbal medicine, and differences in types of CAM modalities used were found between the group with a higher rating of self-perceived disease severity and the lower perceived severity group.

Conclusions
High prevalence of CAM use among infertile women was observed in Korea. Our findings support that infertile women’s own understanding of their illness and physical condition influences self-care behavior such as CAM use. This calls for an urgent need for further in-depth study of the clinical effects of popular CAM modalities among infertile women when used in conjunction with conventional treatment.
A data-driven approach to predicting diabetes and cardiovascular disease with machine learning
Authors: Dinh An , Miertschin Stacey , Young Amber , Mohanty Somya D. 
Published: November 2019

AbstractBackgroundDiabetes and cardiovascular disease are two of the main causes of death in the United States. Identifying and predicting these diseases in patients is the first step towards stopping their progression. We evaluate the capabilities of machine learning models in detecting at-risk patients using survey data (and laboratory results), and identify key variables within the data contributing to these diseases among the patients.MethodsOur research explores data-driven approaches which utilize supervised machine learning models to identify patients with such diseases. Using the National Health and Nutrition Examination Survey (NHANES) dataset, we conduct an exhaustive search of all available feature variables within the data to develop models for cardiovascular, prediabetes, and diabetes detection. Using different time-frames and feature sets for the data (based on laboratory data), multiple machine learning models (logistic regression, support vector machines, random forest, and gradient boosting) were evaluated on their classification performance. The models were then combined to develop a weighted ensemble model, capable of leveraging the performance of the disparate models to improve detection accuracy. Information gain of tree-based models was used to identify the key variables within the patient data that contributed to the detection of at-risk patients in each of the diseases classes by the data-learned models.ResultsThe developed ensemble model for cardiovascular disease (based on 131 variables) achieved an Area Under - Receiver Operating Characteristics (AU-ROC) score of 83.1% using no laboratory results, and 83.9% accuracy with laboratory results. In diabetes classification (based on 123 variables), eXtreme Gradient Boost (XGBoost) model achieved an AU-ROC score of 86.2% (without laboratory data) and 95.7% (with laboratory data). For pre-diabetic patients, the ensemble model had the top AU-ROC score of 73.7% (without laboratory data), and for laboratory based data XGBoost performed the best at 84.4%. Top five predictors in diabetes patients were 1) waist size, 2) age, 3) self-reported weight, 4) leg length, and 5) sodium intake. For cardiovascular diseases the models identified 1) age, 2) systolic blood pressure, 3) self-reported weight, 4) occurrence of chest pain, and 5) diastolic blood pressure as key contributors.ConclusionWe conclude machine learned models based on survey questionnaire can provide an automated identification mechanism for patients at risk of diabetes and cardiovascular diseases. We also identify key contributors to the prediction, which can be further explored for their implications on electronic health records.
A machine-learning approach to predict postprandial hypoglycemia
Authors: Seo Wonju , Lee You-Bin , Lee Seunghyun , Jin Sang-Man , Park Sung-Min 
Published: November 2019

Abstract

Background
For an effective artificial pancreas (AP) system and an improved therapeutic intervention with continuous glucose monitoring (CGM), predicting the occurrence of hypoglycemia accurately is very important. While there have been many studies reporting successful algorithms for predicting nocturnal hypoglycemia, predicting postprandial hypoglycemia still remains a challenge due to extreme glucose fluctuations that occur around mealtimes. The goal of this study is to evaluate the feasibility of easy-to-use, computationally efficient machine-learning algorithm to predict postprandial hypoglycemia with a unique feature set.

Methods
We use retrospective CGM datasets of 104 people who had experienced at least one hypoglycemia alert value during a three-day CGM session. The algorithms were developed based on four machine learning models with a unique data-driven feature set: a random forest (RF), a support vector machine using a linear function or a radial basis function, a K-nearest neighbor, and a logistic regression. With 5-fold cross-subject validation, the average performance of each model was calculated to compare and contrast their individual performance. The area under a receiver operating characteristic curve (AUC) and the F1 score were used as the main criterion for evaluating the performance.

Results
In predicting a hypoglycemia alert value with a 30-min prediction horizon, the RF model showed the best performance with the average AUC of 0.966, the average sensitivity of 89.6%, the average specificity of 91.3%, and the average F1 score of 0.543. In addition, the RF showed the better predictive performance for postprandial hypoglycemic events than other models.

Conclusion
In conclusion, we showed that machine-learning algorithms have potential in predicting postprandial hypoglycemia, and the RF model could be a better candidate for the further development of postprandial hypoglycemia prediction algorithm to advance the CGM technology and the AP technology further.