Javad Ghasemi, M. S. Fekri, M. Larizadeh, S. Dabiri, Y. Jahani
Introduction: Lung cancer (LC) is the most common type of cancer and causes of death among males. This study aims to estimate the survival rate of lung cancer patients by employing the benefits of Bayesian modeling in determining factors affecting the survival of lung cancer in Kerman province, Iran. Methods: We conducted a historical cohort study of 195 patients with lung cancer from 2016 to 2018. In this study, we used linear dependent Dirichlet process (LDDP), and employed some results of the previous study as informative prior for better estimation. Results: Of the 195 patients, 160 died. The mean age of patients at the time of diagnosis was 62.43±12.55. The median survival time of patients was 10.4 months. Men accounted for 75.9% of the total patients. One, two, and three-year survival rate was 44.5%, 22.9%, and 16.4%, respectively. The multivariable model results showed that treatments were significant. Other variables had no significant effect. Conclusion: Our study highlights the importance of prompt diagnosis and appropriate treatment in improving the survival rate of lung cancer patients. We found that patients who received at least one usual lung cancer treatment, such as chemotherapy, radiation therapy, or surgery, had higher survival rates compared to those who did not receive any treatment. While our study has some limitations, such as its retrospective design, our use of Bayesian modeling techniques allowed us to effectively incorporate prior information from previous studies to improve estimation accuracy.
{"title":"An Integrative Bayesian Model Analysis of Patient Characteristics and Treatment Variables to Understand Lung Cancer Survival Rates in Kerman Province, Iran","authors":"Javad Ghasemi, M. S. Fekri, M. Larizadeh, S. Dabiri, Y. Jahani","doi":"10.18502/jbe.v8i4.13357","DOIUrl":"https://doi.org/10.18502/jbe.v8i4.13357","url":null,"abstract":"Introduction: Lung cancer (LC) is the most common type of cancer and causes of death among males. This study aims to estimate the survival rate of lung cancer patients by employing the benefits of Bayesian modeling in determining factors affecting the survival of lung cancer in Kerman province, Iran. \u0000Methods: We conducted a historical cohort study of 195 patients with lung cancer from 2016 to 2018. In this study, we used linear dependent Dirichlet process (LDDP), and employed some results of the previous study as informative prior for better estimation. \u0000Results: Of the 195 patients, 160 died. The mean age of patients at the time of diagnosis was 62.43±12.55. The median survival time of patients was 10.4 months. Men accounted for 75.9% of the total patients. One, two, and three-year survival rate was 44.5%, 22.9%, and 16.4%, respectively. The multivariable model results showed that treatments were significant. Other variables had no significant effect. \u0000Conclusion: Our study highlights the importance of prompt diagnosis and appropriate treatment in improving the survival rate of lung cancer patients. We found that patients who received at least one usual lung cancer treatment, such as chemotherapy, radiation therapy, or surgery, had higher survival rates compared to those who did not receive any treatment. While our study has some limitations, such as its retrospective design, our use of Bayesian modeling techniques allowed us to effectively incorporate prior information from previous studies to improve estimation accuracy.","PeriodicalId":34310,"journal":{"name":"Journal of Biostatistics and Epidemiology","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-08-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"48878547","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Introduction: Alexithymia is a psychiatric disorder in which people become emotionally frustrated. This study aims to model the role of depression, anxiety, and stress in alexithymia prediction. Methods: In this cross-sectional study, 260 undergraduate students were selected via multi-stage cluster sampling. The Toronto Alexithymia Scale (TAS-20) and depression, anxiety and stress scale have been used to collect data. The association between qualitative variables was examined using Chi-square test and LASSO logistic regression was fitted for alexithymia prediction. Results: The mean±SD of participants’ age was 20.7±3.2 years. Of all, 197 (75.8%) students were female and 236 (90.8%) were single. According to the cutoff point for TAS-20, 30.8% of the students displayed signs of alexithymia. The rate of alexithymia was significantly higher among males (42.9% versus 26.9%, P=0.02) and among nursing (45.9%) and anesthesia (44.8%) students than other undergraduate students. The proportion of students with anxiety, depression, and stress were 45.0%, 15.8%, and 9.2%, respectively. 51.2% of the depressed students had alexithymia, while only 26.9% of non-depressed students were alexithymic (P=0.002). LASSO logistic regression showed that odds of alexithymia was significantly higher among male students (OR=1.40, 95% CI=1.03, 1.90), students with depression (OR=1.73, 95% CI=1.18, 2.54), students who had anxiety (OR=1.42, 95% CI=1.07, 1.89), and nursing students (OR=1.62, 95% CI=1.07, 2.45). Conclusion: The results of this study indicate the importance role of anxiety and depression in predicting alexithymia. Due to the high prevalence of alexithymia among college students, we suggest the routine evaluation of college students for alexithymia.
{"title":"The Prediction of Alexithymia Using Depression, Anxiety, Stress, and Demographics in Undergraduate Students","authors":"Asma Darvishi, Elaheh Sanjari, H. Shahraki","doi":"10.18502/jbe.v8i4.13356","DOIUrl":"https://doi.org/10.18502/jbe.v8i4.13356","url":null,"abstract":"Introduction: Alexithymia is a psychiatric disorder in which people become emotionally frustrated. This study aims to model the role of depression, anxiety, and stress in alexithymia prediction. \u0000Methods: In this cross-sectional study, 260 undergraduate students were selected via multi-stage cluster sampling. The Toronto Alexithymia Scale (TAS-20) and depression, anxiety and stress scale have been used to collect data. The association between qualitative variables was examined using Chi-square test and LASSO logistic regression was fitted for alexithymia prediction. \u0000Results: The mean±SD of participants’ age was 20.7±3.2 years. Of all, 197 (75.8%) students were female and 236 (90.8%) were single. According to the cutoff point for TAS-20, 30.8% of the students displayed signs of alexithymia. The rate of alexithymia was significantly higher among males (42.9% versus 26.9%, P=0.02) and among nursing (45.9%) and anesthesia (44.8%) students than other undergraduate students. The proportion of students with anxiety, depression, and stress were 45.0%, 15.8%, and 9.2%, respectively. 51.2% of the depressed students had alexithymia, while only 26.9% of non-depressed students were alexithymic (P=0.002). LASSO logistic regression showed that odds of alexithymia was significantly higher among male students (OR=1.40, 95% CI=1.03, 1.90), students with depression (OR=1.73, 95% CI=1.18, 2.54), students who had anxiety (OR=1.42, 95% CI=1.07, 1.89), and nursing students (OR=1.62, 95% CI=1.07, 2.45). \u0000Conclusion: The results of this study indicate the importance role of anxiety and depression in predicting alexithymia. Due to the high prevalence of alexithymia among college students, we suggest the routine evaluation of college students for alexithymia.","PeriodicalId":34310,"journal":{"name":"Journal of Biostatistics and Epidemiology","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-08-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44775694","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Parisa Keshani, Maryam Jalali, Masoumeh Ghoddusi Johari, Ramin Rezaeianzadeh, Seyed Vahid Hosseini, Abbas Rezaianzadeh
Introduction: Oxidative stress contributes to the development of cardiovascular disease. Tools for evaluating the anti-inflammatory and antioxidative characteristics of an individual’s diet as a whole may be valuable for assessing the combined effects of dietary antioxidants on health. This population-based study aimed to investigate the association between dietary antioxidants and cardiac disease.
Methods: In this population-based cross-sectional study, 10439 individuals aged 40-70 years were recruited during 2014-2017 in Kherameh cohort study which is a part of the Prospective Epidemiological Research Studies in Iran (PERSIAN). The food frequency questionnaire (FFQ) with 130 food items was used to assess the dietary intakes. Vitamin A, E, C, selenium, zinc and Manganese intakes were used to compute dietary antioxidant index (DAI) and dietary antioxidant quality score (DAQs). Chi-square and independent sample T-test was used for comparing qualitative and quantitative variables between the groups respectively Logistic regression analysis was applied for evaluating the association between cardiac disease, DAI and DAQS score after adjusting for covariates.
Results: The participants’ mean age was 52.1±8.3 years. Among all, 4356 (41.7%) were overweight and 1892 (18.1%) were obese. According to the results, odds of cardiac diseases decreased by increasing DAI score (OR=0.80, P value<0.001), Odds of cardiac diseases increased by lower DAQS after adjusting for demographic variables including age, sex, BMI, Marital status and hypertension (OR=0.799, P value=0.002).
Conclusion: The role of anti-oxidants in reducing the odds of cardiovascular disease is very important. Our results highlighted that DAQS and DAI had protective effect on the odds of cardiovascular disease. Therefore, it is suggested that anti-oxidants as zinc, manganese, selenium, and vitamins A, E and C should be taken through food to reduce the risk of the disease.
{"title":"The Association between Dietary Antioxidant Indices and Cardiac Disease: Baseline Data of Kharameh Cohort Study","authors":"Parisa Keshani, Maryam Jalali, Masoumeh Ghoddusi Johari, Ramin Rezaeianzadeh, Seyed Vahid Hosseini, Abbas Rezaianzadeh","doi":"10.18502/jbe.v8i4.13358","DOIUrl":"https://doi.org/10.18502/jbe.v8i4.13358","url":null,"abstract":"Introduction: Oxidative stress contributes to the development of cardiovascular disease. Tools for evaluating the anti-inflammatory and antioxidative characteristics of an individual’s diet as a whole may be valuable for assessing the combined effects of dietary antioxidants on health. This population-based study aimed to investigate the association between dietary antioxidants and cardiac disease.
 Methods: In this population-based cross-sectional study, 10439 individuals aged 40-70 years were recruited during 2014-2017 in Kherameh cohort study which is a part of the Prospective Epidemiological Research Studies in Iran (PERSIAN). The food frequency questionnaire (FFQ) with 130 food items was used to assess the dietary intakes. Vitamin A, E, C, selenium, zinc and Manganese intakes were used to compute dietary antioxidant index (DAI) and dietary antioxidant quality score (DAQs). Chi-square and independent sample T-test was used for comparing qualitative and quantitative variables between the groups respectively Logistic regression analysis was applied for evaluating the association between cardiac disease, DAI and DAQS score after adjusting for covariates.
 Results: The participants’ mean age was 52.1±8.3 years. Among all, 4356 (41.7%) were overweight and 1892 (18.1%) were obese. According to the results, odds of cardiac diseases decreased by increasing DAI score (OR=0.80, P value<0.001), Odds of cardiac diseases increased by lower DAQS after adjusting for demographic variables including age, sex, BMI, Marital status and hypertension (OR=0.799, P value=0.002).
 Conclusion: The role of anti-oxidants in reducing the odds of cardiovascular disease is very important. Our results highlighted that DAQS and DAI had protective effect on the odds of cardiovascular disease. Therefore, it is suggested that anti-oxidants as zinc, manganese, selenium, and vitamins A, E and C should be taken through food to reduce the risk of the disease.","PeriodicalId":34310,"journal":{"name":"Journal of Biostatistics and Epidemiology","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-08-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135444077","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
M. Salari, Z. Rahimi, R. Kalantari, Jamshid Jamali
Introduction: Psychological distress (PD) is one of the most common mental disorders in the general population. Psychological distress is considered a public health priority due to its adverse effects on quality of life, health, performance, and productivity. It can also predict several serious mental illnesses, such as depressive disorder and anxiety. In this study, we intend to identify the behavioral pattern of PD in the population of 18 to 65 years old in Mashhad using two methods, K-median and Latent Class Analysis (LCA), and evaluate the agreement between the two methods. Methods: This cross-sectional study was performed on 38058 individuals referred to community health care centers in Mashhad of Iran in 2019. The information used in this study was extracted from Sina Electronic Health Record System (SinaEHR) database. A demographic information checklist and a 6-item Kessler psychological distress scale (K-6) were used for data collection. K-median and LCA were used for data analysis. Results: Out of 38058 participants, 49.3% were women, 86.1% were married, and 63.6% had a diploma and under diploma education. The LCA identified three patterns of PD in answering the items of the K-6 questionnaire, including severe PD (19.7%), low PD (36.7%), and no PD (43.5%). Three clusters were identified by the K-Median method: 1) severe PD (22.0%), 2) low PD (31.1%), and 3) and no PD (46.9%). The agreement between K-Median and LCA was kappa = 0.862. Conclusion: About 20% of people were classified as having severe PD. Both LCA and k-median methods can reasonably identify the latent pattern of PD with significant entropy, and there was almost complete agreement between the two methods in data clustering. Considering the advantages of the LCA, this method is recommended to identify the latent pattern of PD based on the k-6 questionnaire.
{"title":"Evaluating the Agreement between k-median and Latent Class Analysis for Clustering of Psychological Distress Prevalence","authors":"M. Salari, Z. Rahimi, R. Kalantari, Jamshid Jamali","doi":"10.18502/jbe.v8i4.13353","DOIUrl":"https://doi.org/10.18502/jbe.v8i4.13353","url":null,"abstract":"Introduction: Psychological distress (PD) is one of the most common mental disorders in the general population. Psychological distress is considered a public health priority due to its adverse effects on quality of life, health, performance, and productivity. It can also predict several serious mental illnesses, such as depressive disorder and anxiety. In this study, we intend to identify the behavioral pattern of PD in the population of 18 to 65 years old in Mashhad using two methods, K-median and Latent Class Analysis (LCA), and evaluate the agreement between the two methods. \u0000Methods: This cross-sectional study was performed on 38058 individuals referred to community health care centers in Mashhad of Iran in 2019. The information used in this study was extracted from Sina Electronic Health Record System (SinaEHR) database. A demographic information checklist and a 6-item Kessler psychological distress scale (K-6) were used for data collection. K-median and LCA were used for data analysis. \u0000Results: Out of 38058 participants, 49.3% were women, 86.1% were married, and 63.6% had a diploma and under diploma education. The LCA identified three patterns of PD in answering the items of the K-6 questionnaire, including severe PD (19.7%), low PD (36.7%), and no PD (43.5%). Three clusters were identified by the K-Median method: 1) severe PD (22.0%), 2) low PD (31.1%), and 3) and no PD (46.9%). The agreement between K-Median and LCA was kappa = 0.862. \u0000Conclusion: About 20% of people were classified as having severe PD. Both LCA and k-median methods can reasonably identify the latent pattern of PD with significant entropy, and there was almost complete agreement between the two methods in data clustering. Considering the advantages of the LCA, this method is recommended to identify the latent pattern of PD based on the k-6 questionnaire.","PeriodicalId":34310,"journal":{"name":"Journal of Biostatistics and Epidemiology","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-08-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"45260396","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Introduction: Coordinate-based meta-analysis (CBMA) is a standard method for integrating brain functional patterns in neuroimaging studies. CBMA aims to identify convergency in activated brain regions across studies using coordinates of the peak activation (foci). Here, we aimed to introduce a new application of the Gibbs models for the meta-regression of the neuroimaging studies. Methods: We used a dataset acquired from 31 studies by previous work. For each study as well as foci, study features such as SD duration and the average age were extracted. Two widely Gibbs models, Area-interaction and Geyer saturation were fitted on the foci. These models can quantify and test evidence for clusters in foci using an interaction parameter. We included study features in the models to identify their contribution to foci distribution and hence determine sources of the heterogeneity. Results: Our results revealed that latent study-specific features have a moderate contribution to the heterogeneity of foci distribution. However, the effect of age and SD duration was not significant (p<0.001). Additionally, the estimated interaction parameter was 1.34 (p<0.001) which denotes strong evidence of clusters in foci. Conclusion: Overall, this study highlighted the role of the interaction parameter in CBMA. The results of this work suggest that Gibbs models can be considered as a promising tool for neuroimaging meta-analysis.
{"title":"On The Search for Convergence of Functional Brain Patterns across Neuroimaging Studies: A Coordinate-Based Meta-Analysis Using Gibbs Point Process","authors":"M. Mohammadzadeh, M. Tahmasian, A. Rasekhi","doi":"10.18502/jbe.v8i3.12305","DOIUrl":"https://doi.org/10.18502/jbe.v8i3.12305","url":null,"abstract":"Introduction: Coordinate-based meta-analysis (CBMA) is a standard method for integrating brain functional patterns in neuroimaging studies. CBMA aims to identify convergency in activated brain regions across studies using coordinates of the peak activation (foci). Here, we aimed to introduce a new application of the Gibbs models for the meta-regression of the neuroimaging studies. \u0000Methods: We used a dataset acquired from 31 studies by previous work. For each study as well as foci, study features such as SD duration and the average age were extracted. Two widely Gibbs models, Area-interaction and Geyer saturation were fitted on the foci. These models can quantify and test evidence for clusters in foci using an interaction parameter. We included study features in the models to identify their contribution to foci distribution and hence determine sources of the heterogeneity. \u0000Results: Our results revealed that latent study-specific features have a moderate contribution to the heterogeneity of foci distribution. However, the effect of age and SD duration was not significant (p<0.001). Additionally, the estimated interaction parameter was 1.34 (p<0.001) which denotes strong evidence of clusters in foci. \u0000Conclusion: Overall, this study highlighted the role of the interaction parameter in CBMA. The results of this work suggest that Gibbs models can be considered as a promising tool for neuroimaging meta-analysis.","PeriodicalId":34310,"journal":{"name":"Journal of Biostatistics and Epidemiology","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-03-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49301395","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Introduction: Disorders can often lead to physical illness and suffering along with associated functional disability which hampers the overall well-being of a person. Consequently, it can lead to loss of productivity at the workplace, absenteeism, and social isolation which eventually affects the individual and the society. Researchers have found a crucial association between childhood traumatic experiences with developing anxiety or panic disorder. Methods: The purpose of this study is to do a logistic regression on Add health survey data to examine whether a history of childhood abuse tends to lead to a diagnosis of anxiety or panic disorder in later life. Additionally, medical conditions such as ADHD, PTSD or socio-economic conditions, and addiction were also investigated for their possible contribution to developing anxiety or panic disorder. Results: 49.4 % of respondents reported having faced either physical, emotional, or sexual abuse before the age of 18. Among the total respondents, 12.5 % reported having been diagnosed with anxiety disorder and among these individuals, 25.9 % reported having experienced physical abuse, 64.6 % faced emotional abuse, and 10.3 % said they faced sexual abuse earlier in their life. Results from logistic regression indicated gender (OR=2.069; 95% CI 1.627-2.7), race (OR=0.513; 95% CI 1.442-2.634), PTSD (OR=2.087; 95% CI 1.811-4.35), depression (OR 9.857; 95% CI 7.752-12.535) had a significant effect on developing anxiety. Additionally, an individual who experienced any kind of abuse in their childhood is 0.7 times (95% CI 0.527-0.841) more likely to develop the panic disorder later in their life. Results from the unadjusted logistic regression model indicated that individuals who reported a history of childhood abuse have 1.799 times (95% CI 1.473-2.197) higher odds of being diagnosed with anxiety disorder. Interestingly, women have higher odds (OR= 2.039; 95% CI 1.624-2.560) of having anxiety disorder than men if they were a victim of childhood abuse. Respondents who reported to have faced at least one type of abuse have approximately 1.886 (95% CI 1.512-2.354) times’ greater odds of having anxiety than those who didn’t. Consecutively, experiencing the two types of abuse increased the odds to 2.502 (95% CI 1.930-3.244) finally undergoing all three types of abuse increased the odds by more than double in comparison to those who faced a single kind. Conclusion: Childhood emotional abuse was found to be a more significant contributor to anxiety or panic disorder than other types of abuse. Any kind of childhood abuse experience seemed to have a greater effect on the female portion of the respondents in comparison to the males. Hence, to treat anxiety and panic disorders, childhood maltreatment and other mental illnesses like PTSD and depression should be considered by healthcare professionals to ensure optimal care. Furthermore, interventions targeting those issues need to be developed.
疾病通常会导致身体疾病和痛苦，并伴有相关的功能残疾，从而阻碍一个人的整体健康。因此，它可能导致工作场所生产力下降、缺勤和社会孤立，最终影响到个人和社会。研究人员发现，童年创伤经历与发展为焦虑或恐慌症之间存在重要联系。方法:本研究的目的是对Add健康调查数据进行逻辑回归，以检验童年虐待史是否倾向于导致晚年诊断为焦虑或惊恐障碍。此外，研究人员还调查了ADHD、创伤后应激障碍、社会经济状况和成瘾等疾病对焦虑或恐慌症的可能影响。结果:49.4%的受访者报告在18岁之前遭受过身体、情感或性虐待。在所有受访者中，12.5%的人报告被诊断患有焦虑症，在这些人中，25.9%的人报告遭受过身体虐待，64.6%的人遭受过精神虐待，10.3%的人说他们在生命早期遭受过性虐待。logistic回归结果显示性别差异(OR=2.069;95% CI 1.627-2.7)，种族(OR=0.513;95% ci 1.442-2.634)， PTSD (or =2.087;95% CI 1.811-4.35)，抑郁(OR 9.857;95% CI 7.752-12.535)对发展焦虑有显著影响。此外，在童年经历过任何形式虐待的人在以后的生活中患恐慌症的可能性要高出0.7倍(95% CI 0.527-0.841)。未经调整的logistic回归模型结果显示，报告童年虐待史的个体被诊断为焦虑症的几率高出1.799倍(95% CI 1.473-2.197)。有趣的是，女性患病的几率更高(OR= 2.039;(95% CI 1.624-2.560)如果她们是童年虐待的受害者，她们患焦虑症的几率比男性高。据报道，至少遭受过一种虐待的受访者患焦虑症的几率大约是没有遭受虐待者的1.886倍(95% CI 1.512-2.354)。连续地，经历两种类型的虐待的几率增加到2.502 (95% CI 1.930-3.244)，最后经历所有三种类型的虐待的几率比面对单一类型的人增加了一倍多。结论:儿童时期的情绪虐待比其他类型的虐待对焦虑或惊恐障碍的影响更大。与男性相比，任何形式的童年虐待经历似乎对受访者中女性的影响更大。因此，医疗保健专业人员应该考虑治疗焦虑和恐慌症、儿童虐待和其他精神疾病，如创伤后应激障碍和抑郁症，以确保最佳护理。此外，需要制定针对这些问题的干预措施。
{"title":"Study of Childhood Abuse and Anxiety: An Application of Logistic Regression","authors":"Sultana Mubarika Rahman Chowdhury, Florence George, Sneh Gulati","doi":"10.18502/jbe.v8i3.12307","DOIUrl":"https://doi.org/10.18502/jbe.v8i3.12307","url":null,"abstract":"Introduction: Disorders can often lead to physical illness and suffering along with associated functional disability which hampers the overall well-being of a person. Consequently, it can lead to loss of productivity at the workplace, absenteeism, and social isolation which eventually affects the individual and the society. Researchers have found a crucial association between childhood traumatic experiences with developing anxiety or panic disorder. \u0000Methods: The purpose of this study is to do a logistic regression on Add health survey data to examine whether a history of childhood abuse tends to lead to a diagnosis of anxiety or panic disorder in later life. Additionally, medical conditions such as ADHD, PTSD or socio-economic conditions, and addiction were also investigated for their possible contribution to developing anxiety or panic disorder. \u0000Results: 49.4 % of respondents reported having faced either physical, emotional, or sexual abuse before the age of 18. Among the total respondents, 12.5 % reported having been diagnosed with anxiety disorder and among these individuals, 25.9 % reported having experienced physical abuse, 64.6 % faced emotional abuse, and 10.3 % said they faced sexual abuse earlier in their life. Results from logistic regression indicated gender (OR=2.069; 95% CI 1.627-2.7), race (OR=0.513; 95% CI 1.442-2.634), PTSD (OR=2.087; 95% CI 1.811-4.35), depression (OR 9.857; 95% CI 7.752-12.535) had a significant effect on developing anxiety. Additionally, an individual who experienced any kind of abuse in their childhood is 0.7 times (95% CI 0.527-0.841) more likely to develop the panic disorder later in their life. Results from the unadjusted logistic regression model indicated that individuals who reported a history of childhood abuse have 1.799 times (95% CI 1.473-2.197) higher odds of being diagnosed with anxiety disorder. Interestingly, women have higher odds (OR= 2.039; 95% CI 1.624-2.560) of having anxiety disorder than men if they were a victim of childhood abuse. Respondents who reported to have faced at least one type of abuse have approximately 1.886 (95% CI 1.512-2.354) times’ greater odds of having anxiety than those who didn’t. Consecutively, experiencing the two types of abuse increased the odds to 2.502 (95% CI 1.930-3.244) finally undergoing all three types of abuse increased the odds by more than double in comparison to those who faced a single kind. \u0000Conclusion: Childhood emotional abuse was found to be a more significant contributor to anxiety or panic disorder than other types of abuse. Any kind of childhood abuse experience seemed to have a greater effect on the female portion of the respondents in comparison to the males. Hence, to treat anxiety and panic disorders, childhood maltreatment and other mental illnesses like PTSD and depression should be considered by healthcare professionals to ensure optimal care. Furthermore, interventions targeting those issues need to be developed.","PeriodicalId":34310,"journal":{"name":"Journal of Biostatistics and Epidemiology","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-03-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"47181163","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Zahra Arab Borzu, A. Baghestani, E. Talebi Ghane, Aliakbar Khadem Maboudi, A. Akhavan, A. Saeedi
Introduction: Recurrent event data are common in many longitudinal studies. Often, a terminating event such as death can be correlated with the recurrent event process. A shared frailty model applied to account for the association between recurrent and terminal events. In some situations, a fraction of subjects experience neither recurrent events nor death; these subjects are cured. Methods: In this paper, we discussed the Bayesian approach of a joint frailty model for recurrent and terminal events in the presence of cure fraction. We compared estimates of parameters in the Frequentist and Bayesian approaches via simulation studies in various sample sizes; we applied the joint frailty model in the presence of cure fraction with Frequentist and Bayesian approaches for breast cancer. Results: In small sample size Bayesian approach compared to Frequentist approach had a smaller standard error and mean square error, and the coverage probabilities close to nominal level of 95%. Also, in Bayesian approach, the sampling means of the estimated standard errors were close to the empirical standard error. Conclusion: The simulation results suggested that when sample size was small, the use of Bayesian joint frailty model in the presence of cure fraction led to more efficiency in parameter estimation and statistical inference.
{"title":"Joint Frailty Model of Recurrent and Terminal Events in the Presence of Cure Fraction using a Bayesian Approach","authors":"Zahra Arab Borzu, A. Baghestani, E. Talebi Ghane, Aliakbar Khadem Maboudi, A. Akhavan, A. Saeedi","doi":"10.18502/jbe.v8i3.12306","DOIUrl":"https://doi.org/10.18502/jbe.v8i3.12306","url":null,"abstract":"Introduction: Recurrent event data are common in many longitudinal studies. Often, a terminating event such as death can be correlated with the recurrent event process. A shared frailty model applied to account for the association between recurrent and terminal events. In some situations, a fraction of subjects experience neither recurrent events nor death; these subjects are cured. \u0000Methods: In this paper, we discussed the Bayesian approach of a joint frailty model for recurrent and terminal events in the presence of cure fraction. We compared estimates of parameters in the Frequentist and Bayesian approaches via simulation studies in various sample sizes; we applied the joint frailty model in the presence of cure fraction with Frequentist and Bayesian approaches for breast cancer. \u0000Results: In small sample size Bayesian approach compared to Frequentist approach had a smaller standard error and mean square error, and the coverage probabilities close to nominal level of 95%. Also, in Bayesian approach, the sampling means of the estimated standard errors were close to the empirical standard error. \u0000Conclusion: The simulation results suggested that when sample size was small, the use of Bayesian joint frailty model in the presence of cure fraction led to more efficiency in parameter estimation and statistical inference.","PeriodicalId":34310,"journal":{"name":"Journal of Biostatistics and Epidemiology","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-03-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"45689262","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Introduction: Haplotype analysis allows higher resolution analysis in genetic association studies and is used as a reference panel for genotype imputation in genome-wide association studies. Haplotypes estimates from genotypes among unrelated individuals but misclassification of the haplotype reconstruction will directly affect the accuracy of the results. Methods: This study proposes a novel statistical method Gibbs sampler algorithm to estimate haplotype frequency and quantify the influence of misclassification bias of the estimate haplotype. The performance of the algorithm is evaluated on simulated datasets assuming that linkage phase unknown. The simulation used different minor allele frequencies at each single nucleotide polymorphism (SNP) and different linkagedisequilibrium between the SNPs. Results: The Gibbs sampler algorithm presents higher accuracy among over seven SNPs or less, validated, and deals with missing genotype compared to previous related statistical approaches. Misclassification of estimated haplotypes leads to non-differential bias in exposure and affects haplotype estimates in haplotype analysis. The observed odds ratio underestimates the association between haplotype and phenotype by 36% to 99%. Conclusion: The Gibbs sampler algorithm provides higher accuracy and robust effectiveness performance, handles missing genotypes and provides uncertain probabilities of haplotype frequencies. The misclassification bias of the estimate haplotype underestimates the genetic association by more than forty percent.
{"title":"Non-Parametric MCMC Gibbs Sampler Approach and Misclassification Assessment of Estimating Haplotype Frequencies among Related Statistical Approaches","authors":"G. Ken-Dror, Pankaj Sharma","doi":"10.18502/jbe.v8i3.12304","DOIUrl":"https://doi.org/10.18502/jbe.v8i3.12304","url":null,"abstract":"Introduction: Haplotype analysis allows higher resolution analysis in genetic association studies and is used as a reference panel for genotype imputation in genome-wide association studies. Haplotypes estimates from genotypes among unrelated individuals but misclassification of the haplotype reconstruction will directly affect the accuracy of the results. \u0000Methods: This study proposes a novel statistical method Gibbs sampler algorithm to estimate haplotype frequency and quantify the influence of misclassification bias of the estimate haplotype. The performance of the algorithm is evaluated on simulated datasets assuming that linkage phase unknown. The simulation used different minor allele frequencies at each single nucleotide polymorphism (SNP) and different linkagedisequilibrium between the SNPs. \u0000Results: The Gibbs sampler algorithm presents higher accuracy among over seven SNPs or less, validated, and deals with missing genotype compared to previous related statistical approaches. Misclassification of estimated haplotypes leads to non-differential bias in exposure and affects haplotype estimates in haplotype analysis. The observed odds ratio underestimates the association between haplotype and phenotype by 36% to 99%. \u0000Conclusion: The Gibbs sampler algorithm provides higher accuracy and robust effectiveness performance, handles missing genotypes and provides uncertain probabilities of haplotype frequencies. The misclassification bias of the estimate haplotype underestimates the genetic association by more than forty percent.","PeriodicalId":34310,"journal":{"name":"Journal of Biostatistics and Epidemiology","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-03-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42313606","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Introduction: Anemia is a major public health problem, affecting more than 56 million women worldwide. During pregnancy, hemoglobin concentrations in venous blood below 11 grams per deciliter have significant adverse effects on the health of pregnant women. The main purpose of this study was to investigate the anemia status of the participants and the factors that lead to anemia. Methods: Data for this study were obtained from the 2016 Ethiopian Demographic Health Survey (January 18, 2016, to June 27, 2016). A total of 1053 pregnant women were included in the analysis. The risk factors for anemia status were analyzed using a partial-proportional odds model. Results: The study included 1053 pregnant women, with 32, 214, and 395 suffering from severe, moderate, and mild anemia, respectively. Somalia had the highest proportion of severely anemic people, while Tigray had the lowest. The effect changing in different regions of the sample had various effects on the outcome variable. For example, in the Somali region, the probability of subjects with severe anemia increased by 0.027 (AMPE= 0.027, P = 0.015) percentage points when compared to their counterparts. The effect of changing iron-taking status by one percent on average across the sample decreased by 1.6% (AMPE = -0.016, P= 0.001), 3.7% (AMPE = -0.037, P = 0.001), and 3% (AMPE = -0.030, P = 0.003) points, respectively, for participants in the severe, moderate, and mild classes. The effect of changing place of residence and parity decreased for those in the non-anemic group, but it increased for the wealth index (richest household). Anemia decreased with higher education level [primary: (AMPE = 0.032, P = 0.002), secondary: (AMPE = 0.069, P = 0.025), higher: (AMPE = 0.176, P = 0.000)]. Conclusion: Finally, the authors concluded that iron intake, educational status, wealth index (richest households), place of residence, parity, and selected regions have been identified as prognostic factors for anemia status in pregnant women aged 15 to 49 years. Therefore, action on these predictors is needed to improve anemia among pregnant women in Ethiopia. Furthermore, AMPE should be used with greater motivation to interpret the logistic regression results.
{"title":"Determinants of Anemia Status Among Reproductive Age Women During Pregnancy In Ethiopia: Cross-Sectional Study Design","authors":"A. Legesse, Meskerem Abebe","doi":"10.18502/jbe.v8i3.12308","DOIUrl":"https://doi.org/10.18502/jbe.v8i3.12308","url":null,"abstract":"Introduction: Anemia is a major public health problem, affecting more than 56 million women worldwide. During pregnancy, hemoglobin concentrations in venous blood below 11 grams per deciliter have significant adverse effects on the health of pregnant women. The main purpose of this study was to investigate the anemia status of the participants and the factors that lead to anemia. \u0000Methods: Data for this study were obtained from the 2016 Ethiopian Demographic Health Survey (January 18, 2016, to June 27, 2016). A total of 1053 pregnant women were included in the analysis. The risk factors for anemia status were analyzed using a partial-proportional odds model. \u0000Results: The study included 1053 pregnant women, with 32, 214, and 395 suffering from severe, moderate, and mild anemia, respectively. Somalia had the highest proportion of severely anemic people, while Tigray had the lowest. The effect changing in different regions of the sample had various effects on the outcome variable. For example, in the Somali region, the probability of subjects with severe anemia increased by 0.027 (AMPE= 0.027, P = 0.015) percentage points when compared to their counterparts. The effect of changing iron-taking status by one percent on average across the sample decreased by 1.6% (AMPE = -0.016, P= 0.001), 3.7% (AMPE = -0.037, P = 0.001), and 3% (AMPE = -0.030, P = 0.003) points, respectively, for participants in the severe, moderate, and mild classes. The effect of changing place of residence and parity decreased for those in the non-anemic group, but it increased for the wealth index (richest household). Anemia decreased with higher education level [primary: (AMPE = 0.032, P = 0.002), secondary: (AMPE = 0.069, P = 0.025), higher: (AMPE = 0.176, P = 0.000)]. \u0000Conclusion: Finally, the authors concluded that iron intake, educational status, wealth index (richest households), place of residence, parity, and selected regions have been identified as prognostic factors for anemia status in pregnant women aged 15 to 49 years. Therefore, action on these predictors is needed to improve anemia among pregnant women in Ethiopia. Furthermore, AMPE should be used with greater motivation to interpret the logistic regression results.","PeriodicalId":34310,"journal":{"name":"Journal of Biostatistics and Epidemiology","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-03-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49567353","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
R. Sadeghi, H. Esmaily, Saeedeh Hajebi Khaniki, S. Shahid Sales, Vahid Ghavami
Introduction: Colorectal cancer is the most common cause of cancer mortality in Iran. There are differences in the etiology, clinical behavior and pathological features in cancer of the colon versus the rectum. The aim of this study was to evaluate the factors related to survival and cure probability of patients with colon and rectal cancer using a semi-parametric non-mixture cure rate model. Methods: This retrospective cohort study was conducted on 311 patients, with colorectal cancer. Data of all patients with colon and rectum malignances who underwent the first treatment in Omid Hospital, Mashhad, between 2006 and 2011 were gathered through medical records. Patients were followed-up for 9 years until September 2020. Semi-parametric non-mixture cure model was implemented using miCoPTCM package in the R software. Results: The mean survival time was 2973.94 days (95% confidence interval [CI]: (2694.96, 3252.93). The 5-year survival rates for colon and rectal cancer patients were 0.54 (%95 CI:(0.45, 0.61)) and 0.57 (%95 CI:(0.48,0.65)), respectively. The proportion of cured colon cancer patients was 44.0%, while it was 40.0% for the ones with rectal cancer. Age and stage of the disease were determined as the common related factors of survival and cure fraction for both colon and rectal cancers. Ethnicity and type of first treatment were distinguished as factors related to survival and cure fraction of rectal cancer. Whereas the history of drug abuse increased the hazard of death in colon cancer patients; Also, overweight played a protective role in the survival and cure fraction of rectal cancer patients. Conclusion: Because the factors associated with colorectal cancer are not necessarily equal to the risk factors for colon and rectal cancer, it is recommended to obtain more accurate and valid results in the survival analysis of colorectal cancer patients, the colon and rectum should be considered separately. It is also appropriate to use cure rate models when there is a cure fraction in the data.
{"title":"Analyzing the Long-Term Survival of Colon and Rectal Cancer Patients Using Non-Mixture Cure Rate Model","authors":"R. Sadeghi, H. Esmaily, Saeedeh Hajebi Khaniki, S. Shahid Sales, Vahid Ghavami","doi":"10.18502/jbe.v8i3.12302","DOIUrl":"https://doi.org/10.18502/jbe.v8i3.12302","url":null,"abstract":"Introduction: Colorectal cancer is the most common cause of cancer mortality in Iran. There are differences in the etiology, clinical behavior and pathological features in cancer of the colon versus the rectum. The aim of this study was to evaluate the factors related to survival and cure probability of patients with colon and rectal cancer using a semi-parametric non-mixture cure rate model. \u0000Methods: This retrospective cohort study was conducted on 311 patients, with colorectal cancer. Data of all patients with colon and rectum malignances who underwent the first treatment in Omid Hospital, Mashhad, between 2006 and 2011 were gathered through medical records. Patients were followed-up for 9 years until September 2020. Semi-parametric non-mixture cure model was implemented using miCoPTCM package in the R software. \u0000Results: The mean survival time was 2973.94 days (95% confidence interval [CI]: (2694.96, 3252.93). The 5-year survival rates for colon and rectal cancer patients were 0.54 (%95 CI:(0.45, 0.61)) and 0.57 (%95 CI:(0.48,0.65)), respectively. The proportion of cured colon cancer patients was 44.0%, while it was 40.0% for the ones with rectal cancer. Age and stage of the disease were determined as the common related factors of survival and cure fraction for both colon and rectal cancers. Ethnicity and type of first treatment were distinguished as factors related to survival and cure fraction of rectal cancer. Whereas the history of drug abuse increased the hazard of death in colon cancer patients; Also, overweight played a protective role in the survival and cure fraction of rectal cancer patients. \u0000Conclusion: Because the factors associated with colorectal cancer are not necessarily equal to the risk factors for colon and rectal cancer, it is recommended to obtain more accurate and valid results in the survival analysis of colorectal cancer patients, the colon and rectum should be considered separately. It is also appropriate to use cure rate models when there is a cure fraction in the data.","PeriodicalId":34310,"journal":{"name":"Journal of Biostatistics and Epidemiology","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-03-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"47115295","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
京公网安备 11010802042870号
京ICP备2023020795号-1
扫码关注我们
求助内容：
应助结果提醒方式：