Evaluation of common variants in the CNR2 gene and its interaction with abdominal obesity for osteoporosis susceptibility in Chinese post-menopausal females

Objectives The objective of this study was to investigate the association of four single-nucleotide polymorphisms (SNPs) of the cannabinoid receptor 2 (CNR2) gene, gene-obesity interaction, and haplotype combination with osteoporosis (OP) susceptibility. Methods Chinese patients with OP were recruited between March 2011 and December 2015 from our hospital. In this study, a total of 1267 post-menopausal female patients (631 OP patients and 636 control patients) were selected. The mean age of all subjects was 69.2 years (sd 15.8). A generalized multifactor dimensionality reduction (GMDR) model and logistic regression model were used to examine the interaction between SNP and obesity on OP. For OP patient-control haplotype analyses, the SHEsis online haplotype analysis software ( http://analysis.bio-x.cn/ ) was employed. Results The logistic regression model revealed that the C allele of rs2501431 and the G allele of rs3003336 were associated with increased OP risk, compared with those with wild genotype. However, no significant correlations were found when analyzing the association of rs4237 and rs2229579 with OP risk. The GMDR analysis suggested that the interaction model composed of two factors, rs3003336 and abdominal obesity (AO), was the best model with statistical significance (p-value from sign test (Psign) = 0.012), indicating a potential gene-environment interaction between rs3003336 and AO. Overall, the two-locus models had a cross-validation consistency of 10/10 and had a testing accuracy of 0.641. Abdominally obese subjects with the AG or GG genotype have the highest OP risk, compared with subjects with the AA genotype and normal waist circumference (WC) (odds ratio (OR) 2.23, 95% confidence interval (CI) 1.54 to 3.51). Haplotype analysis also indicated that the haplotype containing the rs3003336-G and rs2501431-C alleles was associated with a statistically increased OP risk. Conclusion Our results suggested that the C allele of rs2501431 and the G allele of rs3003336 of the CNR2 gene, interaction between rs3003336 and AO, and the haplotype containing the rs3003336-G and rs2501431-C alleles were all associated with increased OP risk. Cite this article: Bone Joint Res 2019;8:544–549.

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Haplotype analysis on correlation between transcription factor 7-like 2 gene polymorphism and breast cancer risk

BMC Cancer ◽

10.1186/s12885-021-08571-4 ◽

2021 ◽

Vol 21 (1) ◽

Author(s):

Yang Wang ◽

Xiaojuan Men ◽

Yongxue Gu ◽

Huidong Wang ◽

Zhicai Xu

Keyword(s):

Breast Cancer ◽

Transcription Factor ◽

Logistic Regression ◽

Abdominal Obesity ◽

Haplotype Analysis ◽

Environment Interaction ◽

Nucleotide Polymorphisms ◽

Chinese Han ◽

Locus Model ◽

Gene Environment

Abstract Background Up to now, limited researches focused on the association between transcription factor 7-like 2 gene (TF7L2) gene single nucleotide polymorphisms (SNPs) and breast cancer (BC) risk. The aim of this study was to evaluate the associations between TF7L2 and BC risk in Chinese Han population. Methods Logistic regression model was used to test the correlation between polymorphisms and BC risk. Strength of association was evaluated by odds ratio (OR) and 95% confidence interval (CI). Generalized multifactor dimensionality reduction (GMDR) was applied to analyze the SNP-SNP and gene-environment interaction. Results Logistic regression analysis indicated that the BC risk was obviously higher in carriers of rs1225404 polymorphism C allele than that in TT genotype carriers (TC or CC versus TT), adjusted OR (95%CI) =1.40 (1.09–1.72). Additionally, we also discovered that people with rs7903146- T allele had an obviously higher risk of BC than people with CC allele (CT or TT versus CC), adjusted OR (95%CI) =1.44 (1.09–1.82). GMDR model was used to research the effect of interaction among 4 SNPs and environmental factors on BC risk. We discovered an important two-locus model (p = 0.0100) including rs1225404 and abdominal obesity, suggesting a potential gene–environment correlation between rs1225404 and abdominal obesity. In general, the cross-validation consistency of two-locus model was 10 of 10, and the testing accuracy was 0.632. Compared with subjects with normal waist circumference (WC) value and rs1225404 TT genotype, abdominal obese subjects with rs1225404 TC or CC genotype had the highest BC risk. After covariate adjustment, OR (95%CI) was 2.23 (1.62–2.89). Haplotype analysis indicated that haplotype containing rs1225404-T and rs7903146-C alleles were associated with higher BC risk. Conclusions C allele of rs1225404 and T allele of rs7903146, interaction between rs1225404 and abdominal obesity, rs1225404-T and rs7903146-C haplotype were all related to increased BC risk.

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Evaluation of Workload and Human Errors in Nurses

Archives of Occupational Health ◽

10.18502/aoh.v3i1.346 ◽

2019 ◽

Author(s):

Mahshid Naseri Karimvand ◽

Naser Hasheminejad ◽

Ali Faghihi Zarandi ◽

Yones Jahani

Keyword(s):

Logistic Regression ◽

Regression Model ◽

Human Error ◽

Logistic Regression Model ◽

Control Strategies ◽

Statistical Significance ◽

Medical Sciences ◽

Related Factors ◽

Human Errors ◽

Significance Level

Background: Identification of human errors and their related factors in nurses dealing with the health of humans is important. Considering that much workload can increase the risk of human error, this study aimed to investigate the relationship between workload and human errors among nurses working in educational hospitals of Kerman University of Medical Sciences. Methods: This descriptive-analytical study was performed on 145 nurses from educational hospitals affiliated to Kerman University of Medical Sciences in 20. The workload was evaluated using the NASA-TLX questionnaire and human errors with SHERPA technique. The statistical test used was logistic regression model and the statistical significance level was considered <0.05 and the samples were selected randomly. The sample size was selected based on the percentage of functional errors reported by a study on human error assessment related to the duties of nurses in Semnan. Results: A total of 138 probable errors were detected in the nursing staff of these hospitals, 74% of nurses committed errors in seven main duties during their service. Patient medication with the highest frequency (34%) followed by the injection of the drug to the patient with a frequency of 23% were the most frequently committed errors by nurses. The findings of the research showed that workload in 53.1% of the nurses was very high and in 43.1% of the nurses was high, the results of the logistic regression model showed that there was no significant relationship between errors and workload in nurses. Conclusion: The results of the study showed that the average workload and human error in the nurses were high. Therefore, control strategies such as holding training sessions, implementation of clinical governance program in all wards, recruitment of adequate nurses, reduction of workload, reduction of work hours and the appropriate patient/nurse ratio should be given attention by the hospital managers depending on conditions; as well as the prevention of the two reported errors should be given top priority in corrective measures.

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Risk assessment of severe tricyclic antidepressant overdose

Human & Experimental Toxicology ◽

10.1177/0960327109106970 ◽

2009 ◽

Vol 28 (8) ◽

pp. 511-519 ◽

Cited By ~ 11

Author(s):

Florian Eyer ◽

Jochen Stenzel ◽

Tibor Schuster ◽

Norbert Felgenhauer ◽

Rudi Pfab ◽

...

Keyword(s):

Risk Assessment ◽

Logistic Regression ◽

Regression Model ◽

Clinical Characteristics ◽

Logistic Regression Model ◽

Early Stage ◽

Statistical Significance ◽

Time Lag ◽

Tricyclic Antidepressant ◽

Multivariable Logistic Regression Model

Prognostic factors for severe complications in tricyclic antidepressant (TCA) overdose remain unclear. We therefore evaluated the value of clinical characteristics and electrocardiograph (ECG) parameters to predict serious events (seizures, arrhythmia, death) in severe TCA overdose of 100 patients using logistic regression models for risk assessment. The overall fatality rate was 6%, arrhythmia occurred in 21% and 31% of the patients developed seizures. Using an univariable logistic regression model, the maximal QRS interval (OR 1.22; 95% CI 1.06-1.41; p = .005), the time lag between ingestion and occurrence of first symptoms of overdose (OR 1.13; 95% CI 0.99-1.29; p = .072) and the age (OR 0.73; 95% CI 0.55-0.98; p = .038) were determined as the solely predictive parameters. In the multivariable logistic regression model, the QRS interval could not be established as independent predictor, however, the terminal 40-ms frontal plane QRS vector (T40) reached statistical significance regarding prediction of serious events (odds ration [OR] 1.70; 95% confidence interval [CI] 1.02-2.84; p = .041), along with age and time lag between ingestion and onset of symptoms of overdose with a sensitivity and specificity of 71% and 70%, respectively. Evaluation of both clinical characteristics and ECG-parameters in the early stage of TCA overdose may help to identify those patients who urgently need further aggressive medical observation and management.

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Sub-fecundity and associated factors among mothers with natural planned conception attending antenatal care service in Arba Minch Health Facilities

PLoS ONE ◽

10.1371/journal.pone.0241995 ◽

2020 ◽

Vol 15 (11) ◽

pp. e0241995

Author(s):

Jira Wakoya Feyisa ◽

Sultan Hussen Hebo ◽

Firdawek Getahun Negash ◽

Negussie Boti Sidamo ◽

Kabtamu Tolosie Gergiso ◽

...

Keyword(s):

Logistic Regression ◽

Regression Model ◽

Associated Factors ◽

Logistic Regression Model ◽

Statistical Significance ◽

Coffee Consumption ◽

Health Facilities ◽

Systematic Sampling ◽

P Value ◽

Coital Frequency

Background Fecundity is a physiological ability to have children. The inability to get the desired child which was commonly caused by the prolonged time to conceive due to unwanted non-conception period increased from time to time. As a result, many couples are developing psychological, social, and economic problems and unstable life. However, information on fecundity status is limited in Ethiopia context. Therefore, this study aimed to assess the proportion of sub-fecundity and associated factors in Ethiopia context. Methods A health institution based cross-sectional study was conducted in Arba Minch health facilities from March 25 to April 25, 2020. By using a systematic sampling method, 539 mothers were selected for the study. Structured questionnaire was used for data collection. A binary logistic regression model was used to identify factors associated with the sub-fecundity. Variables with p-value <0.25 in the bi-variable logistic regression analysis were interred and checked for association in a multivariable logistic regression model. The level of statistical significance was declared at p-value <0.05. Result The proportion of sub-fecundity was 17.8% with 95%CI (14.8%-21.3%). Mothers’ age ≥ 30 (AOR = 2.54, 95%CI; 1.18–5.48), partners’ age ≥ 35 (AOR = 2.20, 95%CI; 1.01–4.75), coffee consumption of ≥ 4 cups/day (AOR = 2.93, 95%CI; 1.14–7.53), menses irregularity (AOR = 3.79 95%CI; 2.01–7.14) and coital frequency of 1day/week (AOR = 3.65, 95%CI; 1.47–9.05) were significantly associated with the sub-fecundity. Conclusion This study found that a substantial proportion of mothers were sub-fecund. Factors that contributed to the sub-fecundity were pre-pregnancy; mothers’ age, partners’ age, coffee drinking of ≥ 4 cups/day, coital frequency of 1day/week, and menses irregularity. Thus, efforts to prevent sub-fecundity should focus on awareness creation as to plan to conceive at early age, reducing coffee consumption, increasing days of coital frequency per week, and investigating and treating mothers with irregular menses.

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Fractal Analysis May Improve the Preoperative Identification of Atypical Meningiomas

Neurosurgery ◽

10.1093/neuros/nyw030 ◽

2016 ◽

Vol 80 (2) ◽

pp. 300-308 ◽

Cited By ~ 7

Author(s):

Marcin Czyz ◽

Hesham Radwan ◽

Jian Y. Li ◽

Christopher G. Filippi ◽

Tomasz Tykocki ◽

...

Keyword(s):

Logistic Regression ◽

Fractal Dimension ◽

Regression Model ◽

Fractal Analysis ◽

Logistic Regression Model ◽

Statistical Significance ◽

Multivariate Logistic Regression Model ◽

Benign Meningioma ◽

Who Grade ◽

Atypical Meningiomas

Abstract BACKGROUND: There is no objective and readily accessible method for the preoperative determination of atypical characteristics of a meningioma grade. OBJECTIVE: To evaluate the feasibility of using fractal analysis as an adjunctive tool to conventional radiological techniques in visualizing histopathological features of meningiomas. METHODS: A group of 27 patients diagnosed with atypical (WHO grade II) meningioma and a second group of 27 patients with benign (WHO grade I) meningioma were enrolled in the study. Preoperative brain magnetic resonance (MR) studies (T1-wieghted, post-gadolinium) were processed and analyzed to determine the average fractal dimension (FDa) and maximum fractal dimension (FDm) of the contrast-enhancing region of the tumor using box-count method. FDa and FDm as well as particular radiological features were included in the logistic regression model as possible predictors of malignancy. RESULTS: The cohort consisted of 34 women and 20 men, mean age of 62 ± 15 yr. Fractal analysis showed good interobserver reproducibility (Kappa >0.70). Both FDa and FDm were significantly higher in the atypical compared to the benign meningioma group (P < .0001). Multivariate logistic regression model reached statistical significance with P = .0001 and AUC = 0.87. The FDm, which was greater than 1.31 (odds ratio [OR], 12.30; P = .039), and nonskull base localization (OR, .052; P = .015) were confirmed to be statistically significant predictors of the atypical phenotype. CONCLUSION: Fractal analysis of preoperative MR images appears to be a feasible adjunctive diagnostic tool in identifying meningiomas with potentially aggressive clinical behavior.

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Predicting the Effects of Underage Drinking on Concomitant Alcohol Use Disorder and Poor Educational Attainment

Contemporary Research in Disability and Rehabilitation ◽

10.51734/crdr.v1i1.30 ◽

2018 ◽

Vol 1 (1) ◽

pp. 18-33

Author(s):

Euchay Ngozi Horsman

Keyword(s):

Logistic Regression ◽

Alcohol Use ◽

Educational Attainment ◽

Regression Model ◽

Alcohol Use Disorder ◽

Logistic Regression Model ◽

Statistical Significance ◽

Underage Drinking ◽

Drinking Alcohol ◽

Chi Square

This study examined whether and how underage drinking (UD) relates with concomitant alcohol use disorder and poor educational attainment (CAUDAPEA). A total of 39,860 participants (25-75 years old), roughly 59% of the 2010 National Survey of Drug Use and Health (NSDUH) sample, were drawn for the study. Correlation and regression analyses were used to address the research question. Demographic characteristics of respondents were analyzed using t-test or Chi-square statistics. Alpha was set at .05 to determine statistical significance. Underage drinking alone was a strong and statistically significant predictor of CAUDAPEA. The simple binary logistic regression model identified was statistically significant: (chi-square = 24.19, df =1, p < .05), (Cox and Snell R2 = 0.001), and (Nagelkerke R2 = 0.015), which suggests that using the Nagelkerke R2, the model explains roughly 1.5% of the variation in CAUDAPEA. The regression coefficient and the Wald statistic show that the effect of having underage drinking history (UDHISTORY) on CAUDAPEA is highly significant (Wald F = 14.44, df = 1, p < .05) with odds ratio = 4.86 indicating that currently legal age drinkers with UDHISTORY were about five times more likely to experience CAUDAPEA than their counterparts without UDHISTORY. When demographic variables (age, gender, race/ethnicity) were added to the model, the identified final multiple logistic regression model was statistically significant, (chi-square = 132.33, df = 10, p < .05), (Cox and Snell R2 = 0.008), and (Nagelkerke R2 = 0.079) which suggests that using the Nagelkerke R2, the model explains roughly 7.9% of the variance in CAUDAPEA, an improvement over the model with UDHISTORY alone. Results suggest different ways of looking at relationships between underage drinking, alcohol use disorder, and educational attainment. Implications for rehabilitation and prevention are discussed. Keywords: underage drinking, alcohol use disorder, poor educational attainment, concomitance

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