Pub Date : 2018-01-01DOI: 10.4172/2155-6180.1000408
N. Demirkuş, Enes Bilgin, Dilvin Alkan
Mathematics is like a habitat in which all the branches of science flourish. Mathematical Science: Creates the denominator of the Science Cluster. Other branches of science form the shares of the Science Cluster. The Sum of shares and denominator: Represents The Cluster of Science. Mathematical knowledge is like the heart of science. Science without mathematics cannot work. In This Presentation, firstly, the position and definition of mathematics in science will be done. The original definitions of eternity, infinity, death, time and first point concepts and their relations will be given. Later, these concepts will be related to the Big Bang Theory and the Big Rip Theory. Before the The Planck time (10-43 seconds) from the Beginning of Big Bang Theory: The occurrence of time, space, speed and gravitational dimensions will be mathematically related, Information about the starting point of the universe will be given. Mathematical explanations of 4 basic forces in the universe will be done. There are 4 conventionally accepted fundamental interactions: gravitational, electromagnetic force, strong nuclear force and weak nuclear force. As a result, the concepts of Eternity, Infinity, Death, Time, and First Point in mathematics will match the equivalents in the universe. Citation: Demirkuş N, Bilgin EA (2018) A New Approach to the Definitions and Relations of the Concepts of Mathematics, Eternity, Infinity, Death, Time and the First Point. J Biom Biostat 9: 408. doi: 10.4172/2155-6180.1000408
{"title":"A New Approach to the Definitions and Relations of the Concepts of Mathematics, Eternity, Infinity, Death, Time and the First Point","authors":"N. Demirkuş, Enes Bilgin, Dilvin Alkan","doi":"10.4172/2155-6180.1000408","DOIUrl":"https://doi.org/10.4172/2155-6180.1000408","url":null,"abstract":"Mathematics is like a habitat in which all the branches of science flourish. Mathematical Science: Creates the denominator of the Science Cluster. Other branches of science form the shares of the Science Cluster. The Sum of shares and denominator: Represents The Cluster of Science. Mathematical knowledge is like the heart of science. Science without mathematics cannot work. In This Presentation, firstly, the position and definition of mathematics in science will be done. The original definitions of eternity, infinity, death, time and first point concepts and their relations will be given. Later, these concepts will be related to the Big Bang Theory and the Big Rip Theory. Before the The Planck time (10-43 seconds) from the Beginning of Big Bang Theory: The occurrence of time, space, speed and gravitational dimensions will be mathematically related, Information about the starting point of the universe will be given. Mathematical explanations of 4 basic forces in the universe will be done. There are 4 conventionally accepted fundamental interactions: gravitational, electromagnetic force, strong nuclear force and weak nuclear force. As a result, the concepts of Eternity, Infinity, Death, Time, and First Point in mathematics will match the equivalents in the universe. Citation: Demirkuş N, Bilgin EA (2018) A New Approach to the Definitions and Relations of the Concepts of Mathematics, Eternity, Infinity, Death, Time and the First Point. J Biom Biostat 9: 408. doi: 10.4172/2155-6180.1000408","PeriodicalId":87294,"journal":{"name":"Journal of biometrics & biostatistics","volume":"09 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2018-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.4172/2155-6180.1000408","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"70292833","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}
Pub Date : 2017-12-04DOI: 10.4172/2155-6180-C1-005
AnamRiazAbdulBasitZafarIqbal, Munir Ahmad
{"title":"Exponential behavior of health indicators of Pakistan","authors":"AnamRiazAbdulBasitZafarIqbal, Munir Ahmad","doi":"10.4172/2155-6180-C1-005","DOIUrl":"https://doi.org/10.4172/2155-6180-C1-005","url":null,"abstract":"","PeriodicalId":87294,"journal":{"name":"Journal of biometrics & biostatistics","volume":"1 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2017-12-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"70298737","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}
Pub Date : 2017-12-04DOI: 10.4172/2155-6180-C1-006
Ch Sanjay
Statement of the Problem: Dengue fever is a mosquito-borne disease that occurs in tropical and sub-tropical parts of the world. As many as 400 million people are infected yearly. In mild cases, symptoms are fever, rash, and muscle and joint pain, while in severe cases, dengue fever can cause severe bleeding, low blood pressure, and even death (in fact, the first death of dengue fever this year in Hanoi, Vietnam was just reported today, May 22, 2017). Because, it is carried by mosquitoes. The transmission of dengue is related to climate variables such as temperature and precipitation. A growing number of scientists argue that climate change is likely to produce distributional shifts that may cause an increase in the outbreaks of dengue fever and have significant public health implications worldwide. The increased risk of dengue augments the need for accurate models to predict the time, location, and severity of dengue outbreaks in Latin America.
{"title":"Biometric security, E-health care: Indian context","authors":"Ch Sanjay","doi":"10.4172/2155-6180-C1-006","DOIUrl":"https://doi.org/10.4172/2155-6180-C1-006","url":null,"abstract":"Statement of the Problem: Dengue fever is a mosquito-borne disease that occurs in tropical and sub-tropical parts of the world. As many as 400 million people are infected yearly. In mild cases, symptoms are fever, rash, and muscle and joint pain, while in severe cases, dengue fever can cause severe bleeding, low blood pressure, and even death (in fact, the first death of dengue fever this year in Hanoi, Vietnam was just reported today, May 22, 2017). Because, it is carried by mosquitoes. The transmission of dengue is related to climate variables such as temperature and precipitation. A growing number of scientists argue that climate change is likely to produce distributional shifts that may cause an increase in the outbreaks of dengue fever and have significant public health implications worldwide. The increased risk of dengue augments the need for accurate models to predict the time, location, and severity of dengue outbreaks in Latin America.","PeriodicalId":87294,"journal":{"name":"Journal of biometrics & biostatistics","volume":"1 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2017-12-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"70298793","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}
Pub Date : 2017-11-27DOI: 10.4172/2155-6180.1000382
L. Alii
In this paper, analysis was done for patients diagnosed of cancer from the Kilifi county hospital. The presence or absence of breast cancer had been done by the medical personnel and data documented. The objective was to determine the cancer prevalence rates of in the county. Data was obtained from survey questions and diagnosis by the medical personnel within the observation and follow up period of the patients. Data was also obtained for patients that had undergone testing to ascertain the type of tumor they had. Chi-square tests were carried out to check whether there was association between cancer and the smoking and between cancer and alcohol intake. The test show there was no association between Cancer and smoking (χ2=0.70938, df=2, pvalue=0.7014). Similarly a chi-square test showed no association between breast cancer and alcohol intake (χ2=0.42101, df=2, pvalue=0.8102). A logistic regression was fit to adjust for confounding. The table below shows the results after fitting this model. The results confirm that smoking and alcohol intake was not associated with breast cancer.
{"title":"Estimating Prevalence Rates of Women Diagnosed with Breast Cancer in Kilifi County","authors":"L. Alii","doi":"10.4172/2155-6180.1000382","DOIUrl":"https://doi.org/10.4172/2155-6180.1000382","url":null,"abstract":"In this paper, analysis was done for patients diagnosed of cancer from the Kilifi county hospital. The presence or absence of breast cancer had been done by the medical personnel and data documented. The objective was to determine the cancer prevalence rates of in the county. Data was obtained from survey questions and diagnosis by the medical personnel within the observation and follow up period of the patients. Data was also obtained for patients that had undergone testing to ascertain the type of tumor they had. Chi-square tests were carried out to check whether there was association between cancer and the smoking and between cancer and alcohol intake. The test show there was no association between Cancer and smoking (χ2=0.70938, df=2, pvalue=0.7014). Similarly a chi-square test showed no association between breast cancer and alcohol intake (χ2=0.42101, df=2, pvalue=0.8102). A logistic regression was fit to adjust for confounding. The table below shows the results after fitting this model. The results confirm that smoking and alcohol intake was not associated with breast cancer.","PeriodicalId":87294,"journal":{"name":"Journal of biometrics & biostatistics","volume":"8 1","pages":"1-3"},"PeriodicalIF":0.0,"publicationDate":"2017-11-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.4172/2155-6180.1000382","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"48041745","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}
Pub Date : 2017-10-05DOI: 10.4172/2155-6180.1000369
Gesese Melaku Tadege
Background Cardiovascular disease complication is the timely issue throughout the world. Objective of the study The aim of this study is to analysis the major risk factors which lead to cardiovascular disease complication on hypertensive patients. Method A retrospective cohort study with One hundred and fifty-three hypertensive patients have been taken from a hospital record at Felege Hiwot Referral Hospital, Bahir Dar, Ethiopia, during 2012 to 2016. Kaplan-Meier and Cox proportional hazard models were applied. Result From long rank test result, Patients who were live in baseline cardiovascular disease significantly different from patients who hadn’t complication for a shorter cardiovascular disease complication time. From the Cox regression result, the chance of being infected with cardiovascular complication rise through 3.7%, when a single year increment of age (p value=0.0486). The possibility of a patient to develop cardiovascular disease who live in rural were 0.377 times lower than a patient who live in urban (P value=0.0275). The risk of developing cardiovascular complication in a short period of time was 8% and 6% depending on 10 MmHg increment of systolic and diastolic blood pressure respectively. Patients who had baseline complication were found to be associated with shorter survival time within their pain, that hazard ratio was 4.684 times than that of a patient who had not baseline complication(P value=0.0004). Conclusion From Cox proportional hazard model, there were five major factors that affect the cardiovascular disease complication time of hypertension patient those are; residence, baseline cardiovascular complication status, baseline diastolic blood pressure, baseline systolic blood pressure and baseline age at 5% significant level.
{"title":"Survival Analysis of Time to Cardiovascular Disease Complication of Hypertensive Patients at Felege Hiwot Referral Hospital in Bahir-Dar, Ethiopia: A Retrospective Cohort Study","authors":"Gesese Melaku Tadege","doi":"10.4172/2155-6180.1000369","DOIUrl":"https://doi.org/10.4172/2155-6180.1000369","url":null,"abstract":"Background \u0000Cardiovascular disease complication is the timely issue throughout the world. \u0000 Objective of the study \u0000The aim of this study is to analysis the major risk factors which lead to cardiovascular disease complication on hypertensive patients. \u0000 Method \u0000A retrospective cohort study with One hundred and fifty-three hypertensive patients have been taken from a hospital record at Felege Hiwot Referral Hospital, Bahir Dar, Ethiopia, during 2012 to 2016. Kaplan-Meier and Cox proportional hazard models were applied. \u0000Result \u0000From long rank test result, Patients who were live in baseline cardiovascular disease significantly different from patients who hadn’t complication for a shorter cardiovascular disease complication time. From the Cox regression result, the chance of being infected with cardiovascular complication rise through 3.7%, when a single year increment of age (p value=0.0486). The possibility of a patient to develop cardiovascular disease who live in rural were 0.377 times lower than a patient who live in urban (P value=0.0275). The risk of developing cardiovascular complication in a short period of time was 8% and 6% depending on 10 MmHg increment of systolic and diastolic blood pressure respectively. Patients who had baseline complication were found to be associated with shorter survival time within their pain, that hazard ratio was 4.684 times than that of a patient who had not baseline complication(P value=0.0004). \u0000Conclusion \u0000From Cox proportional hazard model, there were five major factors that affect the cardiovascular disease complication time of hypertension patient those are; residence, baseline cardiovascular complication status, baseline diastolic blood pressure, baseline systolic blood pressure and baseline age at 5% significant level.","PeriodicalId":87294,"journal":{"name":"Journal of biometrics & biostatistics","volume":" ","pages":"1-5"},"PeriodicalIF":0.0,"publicationDate":"2017-10-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"48690684","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}
Pub Date : 2017-10-01Epub Date: 2017-10-18DOI: 10.4172/2155-6180.1000375
Adriana Pérez, Lung-Chang Chien, Melissa B Harrell, Keryn E Pasch, Udoka C Obinwa, Cheryl L Perry
Introduction: To identify the geospatial association between the presence of tobacco retail outlets (TRO) around schools' neighborhoods, and current use of cigarettes and e-cigarettes among adolescents in four counties in Texas.
Methods: Students in grades 6, 8 and 10th were surveyed in their schools in 2014-2015. The schools' addresses was geocoded to determine the presence of at least one TRO within half a mile of the school. Two outcomes were considered: past 30-day use of (a) cigarettes and (b) e-cigarettes. Bayesian structured additive regression models and Kriging methods were used to estimate the geospatial associations between the presence of TRO and use in three counties: Dallas/Tarrant, Harris, and Travis.
Results: We observed a geospatial association between the presence of TRO around the schools and current use of cigarettes in the eastern area of Dallas County and in the southeastern area of Harris County. Also, a geospatial association between the presence of TRO around the schools and current use of e-cigarettes was observed in the entire Tarrant County and in the northeastern area of Harris County.
Conclusions: There were geospatial associations between the presence of TRO around some schools and cigarette/e-cigarette use among students, but this association was not consistent across all the counties. More research is needed to determine why some areas are at higher risk for this association.
{"title":"Geospatial Associations Between Tobacco Retail Outlets and Current Use of Cigarettes and e-Cigarettes among Youths in Texas.","authors":"Adriana Pérez, Lung-Chang Chien, Melissa B Harrell, Keryn E Pasch, Udoka C Obinwa, Cheryl L Perry","doi":"10.4172/2155-6180.1000375","DOIUrl":"https://doi.org/10.4172/2155-6180.1000375","url":null,"abstract":"<p><strong>Introduction: </strong>To identify the geospatial association between the presence of tobacco retail outlets (TRO) around schools' neighborhoods, and current use of cigarettes and e-cigarettes among adolescents in four counties in Texas.</p><p><strong>Methods: </strong>Students in grades 6, 8 and 10th were surveyed in their schools in 2014-2015. The schools' addresses was geocoded to determine the presence of at least one TRO within half a mile of the school. Two outcomes were considered: past 30-day use of (a) cigarettes and (b) e-cigarettes. Bayesian structured additive regression models and Kriging methods were used to estimate the geospatial associations between the presence of TRO and use in three counties: Dallas/Tarrant, Harris, and Travis.</p><p><strong>Results: </strong>We observed a geospatial association between the presence of TRO around the schools and current use of cigarettes in the eastern area of Dallas County and in the southeastern area of Harris County. Also, a geospatial association between the presence of TRO around the schools and current use of e-cigarettes was observed in the entire Tarrant County and in the northeastern area of Harris County.</p><p><strong>Conclusions: </strong>There were geospatial associations between the presence of TRO around some schools and cigarette/e-cigarette use among students, but this association was not consistent across all the counties. More research is needed to determine why some areas are at higher risk for this association.</p>","PeriodicalId":87294,"journal":{"name":"Journal of biometrics & biostatistics","volume":"8 5","pages":""},"PeriodicalIF":0.0,"publicationDate":"2017-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.4172/2155-6180.1000375","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"35624397","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2017-08-31DOI: 10.4172/2155-6180.1000365
C. Lancaster, R. Harrison
Bone loss is a major health problem that many aging individuals will face and thus research focusing on enhancing bone formation is of great importance. Cell biology or in vitro studies are particularly useful in exploring the exact effects a vitamin, supplement or drug has on particular processes within a certain cell type. Although there have been many cell biology articles focusing on the effects of vitamin D, K1 or K2 addition on bone formation in vitro, there has yet to be a consensus amongst the literature. The purpose of this article is to determine the effects of vitamin D, K1 and K2 supplementation on osteoblast maturation parameters through meta-analysis of past cell biology literature. A Hedges d effect size was calculated for each experiment extracted from past literature and the experiments were grouped by experiment and cell type. Homogeneity was assessed by the Cochran’s Q test, while the effect sizes’ departure from zero was assessed by a 95% confidence interval and a non-directional test. Supplementation with vitamin D, K1 and K2, along with the combination of vitamin K2+ 1,25-dihydroxyvitamin D, increased bone mineralization, while not consistently affecting all of the other parameters associated with bone formation. Vitamin K2 and D addition had variable effects on bone formation using different cell types, which calls into question the suitability of particular cell lines as models for clinical trials. Therefore, the conditions and parameters in which bone formation is studied in vitro must be considered carefully before running a vitamin supplementation or drug-testing experiment.
{"title":"Effects of Vitamin D, K1, and K2 Supplementation on Bone Formation byOsteoblasts In Vitro: A Meta-analysis","authors":"C. Lancaster, R. Harrison","doi":"10.4172/2155-6180.1000365","DOIUrl":"https://doi.org/10.4172/2155-6180.1000365","url":null,"abstract":"Bone loss is a major health problem that many aging individuals will face and thus research focusing on enhancing bone formation is of great importance. Cell biology or in vitro studies are particularly useful in exploring the exact effects a vitamin, supplement or drug has on particular processes within a certain cell type. Although there have been many cell biology articles focusing on the effects of vitamin D, K1 or K2 addition on bone formation in vitro, there has yet to be a consensus amongst the literature. The purpose of this article is to determine the effects of vitamin D, K1 and K2 supplementation on osteoblast maturation parameters through meta-analysis of past cell biology literature. A Hedges d effect size was calculated for each experiment extracted from past literature and the experiments were grouped by experiment and cell type. Homogeneity was assessed by the Cochran’s Q test, while the effect sizes’ departure from zero was assessed by a 95% confidence interval and a non-directional test. Supplementation with vitamin D, K1 and K2, along with the combination of vitamin K2+ 1,25-dihydroxyvitamin D, increased bone mineralization, while not consistently affecting all of the other parameters associated with bone formation. Vitamin K2 and D addition had variable effects on bone formation using different cell types, which calls into question the suitability of particular cell lines as models for clinical trials. Therefore, the conditions and parameters in which bone formation is studied in vitro must be considered carefully before running a vitamin supplementation or drug-testing experiment.","PeriodicalId":87294,"journal":{"name":"Journal of biometrics & biostatistics","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2017-08-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.4172/2155-6180.1000365","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"48196678","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}
Pub Date : 2017-08-31DOI: 10.4172/2155-6180.1000364
Kesheng Wang, Y. Liu, Xin Xie, Shaoqing Gong, Chun Xu, Zhanxin Sha
The associations of nutrition factors and physical activities with adult diabetes are inconsistent; while most of these factors are inter correlated. The aims of this study are to overcome the disturbance of the multicollinearity of the risk factors and examine the associations of these factors with diabetes using the principal component analysis (PCA) and regression analysis with principal component scores (PCS). Totally, 659 adults with diabetes and 2827 non-diabetic were selected from the 2012 Health Information National Trends Survey (HINTS 4, Cycle 2). PCA was utilized to deal with multicollinearity of the risk factors. Weighted univariate and multiple logistic regression analyses were used to estimate the associations of potential factors and PCS with diabetes. The odds ratios (ORs) with 95% confidence intervals (CIs) were estimated. The first 3 PCs for nutrition factors and physical activities could explain 70% variances. The first principal component (PC1) is a measure of nutrition factors (fruit and vegetables consumption), PC2 is a measure for physical activities (moderate exercise and strength training), and PC3 is about calorie information use and soda use. Weighted multiple logistic regression showed that African Americans, middle aged adults (45-64 years), elderly (65+), never married, and with lower education were associated with increased odds of diabetes. After adjusting for others factors, the PC1 showed marginal association with diabetes (OR=0.84, 95% CI=0.70-1.01); while PC2 and PC3 revealed significant associations with diabetes (OR=0.73, 95% CI=0.61-0.86 and OR=0.85, 95% CI=0.74-0.99, respectively). In conclusion, PCA can be used to reduce the indicators in complex survey data. The first 3 PCs of nutrition factors and physical activities were associated with diabetes. Promotion of health food and physical activities should be encouraged to help decrease the prevalence of diabetes.
{"title":"Principal Component Regression Analysis of Nutrition Factors andPhysical Activities with Diabetes","authors":"Kesheng Wang, Y. Liu, Xin Xie, Shaoqing Gong, Chun Xu, Zhanxin Sha","doi":"10.4172/2155-6180.1000364","DOIUrl":"https://doi.org/10.4172/2155-6180.1000364","url":null,"abstract":"The associations of nutrition factors and physical activities with adult diabetes are inconsistent; while most of these factors are inter correlated. The aims of this study are to overcome the disturbance of the multicollinearity of the risk factors and examine the associations of these factors with diabetes using the principal component analysis (PCA) and regression analysis with principal component scores (PCS). Totally, 659 adults with diabetes and 2827 non-diabetic were selected from the 2012 Health Information National Trends Survey (HINTS 4, Cycle 2). PCA was utilized to deal with multicollinearity of the risk factors. Weighted univariate and multiple logistic regression analyses were used to estimate the associations of potential factors and PCS with diabetes. The odds ratios (ORs) with 95% confidence intervals (CIs) were estimated. The first 3 PCs for nutrition factors and physical activities could explain 70% variances. The first principal component (PC1) is a measure of nutrition factors (fruit and vegetables consumption), PC2 is a measure for physical activities (moderate exercise and strength training), and PC3 is about calorie information use and soda use. Weighted multiple logistic regression showed that African Americans, middle aged adults (45-64 years), elderly (65+), never married, and with lower education were associated with increased odds of diabetes. After adjusting for others factors, the PC1 showed marginal association with diabetes (OR=0.84, 95% CI=0.70-1.01); while PC2 and PC3 revealed significant associations with diabetes (OR=0.73, 95% CI=0.61-0.86 and OR=0.85, 95% CI=0.74-0.99, respectively). In conclusion, PCA can be used to reduce the indicators in complex survey data. The first 3 PCs of nutrition factors and physical activities were associated with diabetes. Promotion of health food and physical activities should be encouraged to help decrease the prevalence of diabetes.","PeriodicalId":87294,"journal":{"name":"Journal of biometrics & biostatistics","volume":"8 1","pages":"1-7"},"PeriodicalIF":0.0,"publicationDate":"2017-08-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"41888506","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}
Pub Date : 2017-08-28DOI: 10.4172/2155-6180.1000366
J. Šteňo, V. Boyko, P. Zamiatin, N. Dubrovina, R. Gerrard, P. Labaš, O. Gurov, O. Kozyreva, D. Hladkykh, Yu. S. Tkachenko, D. Zamiatin, Viktorija Borodina
Background: There are different approaches to the assessment of the severity of trauma in a victim and to the provision of specialized health care. Some of them are based on the development of scales and logistic models, using expert systems or statistical methods, to assess the severity of injury and the probability of a particular outcome. This article presents the results of a study on the feasibility of developing and applying various statistical models in order to predict the outcome in the case of different types of trauma, based on data on the status of victims with severe trauma. Patients and methods: We present selected information about 373 victims, admitted and treated at the Department of Traumatic Shock of the GI «V.T. Zaycev Kharkiv Research Institute of General and Emergency Surgery» of NAMS of Ukraine; the records, which relate to patients with severe and combined trauma, were made between 1985 and 2015. The initial database contained 263 victims who had positive outcomes (survived), while 110 had fatal outcomes. Most of the patients presented with an open trauma (285 cases), then there were 80 cases with a closed injury and only 8 cases with a combined injury. Results: To estimate the probability of the outcome for various types of trauma we have developed a predictive model, based on a logistic relationship. Categorical variables, indicating the presence or absence of various types of trauma, were used in the model. Information about the eventual outcome for a given victim with the indicated type of trauma was used as the dependent variable. The logit model which we obtained has a high predictive accuracy in predicting positive outcomes. Thus, based on the a posteriori analysis, 92% of cases in which victims survived were correctly recognized by the model. In view of the fact that abdominal trauma is the commonest of all trauma mechanisms, we constructed a predictive model to estimate the probability of various outcomes in the case of abdominal trauma or injury to certain organs of the abdominal cavity. Linear discriminant functions were developed by us and used for the classification of possible outcomes depending on the condition of the victim and the resuscitation measures carried out. The model presented has a high predictive accuracy: on the basis of a posteriori analysis using data of discriminant functions, correct conclusions were drawn in 90% of cases when there was a positive outcome, and in 75% of cases when the outcome was fatal. Conclusion: We conclude that it is reasonable to use the statistical model developed, along with other qualitative and quantitative methods of prognostic determination of outcomes for victims with severe injuries. As different models have different predictive accuracy and require the provision of different information, it is necessary to use a sufficiently large number of techniques to derive accurate predictions and to choose the right tactics for diagnosis and treatment.
{"title":"Prediction of Outcomes in Victims with Severe Trauma by StatisticalModels","authors":"J. Šteňo, V. Boyko, P. Zamiatin, N. Dubrovina, R. Gerrard, P. Labaš, O. Gurov, O. Kozyreva, D. Hladkykh, Yu. S. Tkachenko, D. Zamiatin, Viktorija Borodina","doi":"10.4172/2155-6180.1000366","DOIUrl":"https://doi.org/10.4172/2155-6180.1000366","url":null,"abstract":"Background: There are different approaches to the assessment of the severity of trauma in a victim and to the provision of specialized health care. Some of them are based on the development of scales and logistic models, using expert systems or statistical methods, to assess the severity of injury and the probability of a particular outcome. This article presents the results of a study on the feasibility of developing and applying various statistical models in order to predict the outcome in the case of different types of trauma, based on data on the status of victims with severe trauma. Patients and methods: We present selected information about 373 victims, admitted and treated at the Department of Traumatic Shock of the GI «V.T. Zaycev Kharkiv Research Institute of General and Emergency Surgery» of NAMS of Ukraine; the records, which relate to patients with severe and combined trauma, were made between 1985 and 2015. The initial database contained 263 victims who had positive outcomes (survived), while 110 had fatal outcomes. Most of the patients presented with an open trauma (285 cases), then there were 80 cases with a closed injury and only 8 cases with a combined injury. Results: To estimate the probability of the outcome for various types of trauma we have developed a predictive model, based on a logistic relationship. Categorical variables, indicating the presence or absence of various types of trauma, were used in the model. Information about the eventual outcome for a given victim with the indicated type of trauma was used as the dependent variable. The logit model which we obtained has a high predictive accuracy in predicting positive outcomes. Thus, based on the a posteriori analysis, 92% of cases in which victims survived were correctly recognized by the model. In view of the fact that abdominal trauma is the commonest of all trauma mechanisms, we constructed a predictive model to estimate the probability of various outcomes in the case of abdominal trauma or injury to certain organs of the abdominal cavity. Linear discriminant functions were developed by us and used for the classification of possible outcomes depending on the condition of the victim and the resuscitation measures carried out. The model presented has a high predictive accuracy: on the basis of a posteriori analysis using data of discriminant functions, correct conclusions were drawn in 90% of cases when there was a positive outcome, and in 75% of cases when the outcome was fatal. Conclusion: We conclude that it is reasonable to use the statistical model developed, along with other qualitative and quantitative methods of prognostic determination of outcomes for victims with severe injuries. As different models have different predictive accuracy and require the provision of different information, it is necessary to use a sufficiently large number of techniques to derive accurate predictions and to choose the right tactics for diagnosis and treatment.","PeriodicalId":87294,"journal":{"name":"Journal of biometrics & biostatistics","volume":"8 1","pages":"1-5"},"PeriodicalIF":0.0,"publicationDate":"2017-08-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.4172/2155-6180.1000366","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42904775","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}
Pub Date : 2017-08-23DOI: 10.4172/2155-6180.1000367
Baptiste Féraud, Réjane Rousseau, P. Tullio, M. Verleysen, B. Govaerts
In order to maintain life, living organism’s product and transform small molecules called metabolites. Metabolomics aims at studying the development of biological reactions resulting from a contact with a physio-pathological stimulus, through these metabolites. The 1H-NMR spectroscopy is widely used to graphically describe a metabolite composition via spectra. Biologists can then confirm or invalidate the development of a biological reaction if specific NMR spectral regions are altered from a given physiological situation to another. However, this pro-cess supposes a preliminary identification step which traditionally consists in the study of the two first components of a Principal Component Analysis (PCA). This paper presents a new methodology in two main steps providing knowledge on specific 1H-NMR spectral areas via the identification of biomarkers and via the visualization of the effects caused by some external changes. The first step implies Independent Component Analysis (ICA) in order to decompose the spectral data into statistically independent components or sources of information. The in-dependent (pure or composite) metabolites contained in bio fluids are discovered through the sources, and their quantities through mixing weights. Specific questions related to ICA like the choice of the number of components and their ordering are discussed. The second step consists in a statistical modelling of the ICA mixing weights and introduces statistical hypothesis tests on the parameters of the estimated models, with the objective of selecting sources which present biomarkers (or significantly fluctuating spectral regions). Statistical models are considered here for their adaptability to different possible kinds of data or contexts. A computation of contrasts which can lead to the visualization of changes on spectra caused by changes of the factor of interest is also proposed. This methodology is innovative because multi-factors studies (via the use of mixed models) and statistical confirmations of the factors effects are allowed together.
{"title":"Independent Component Analysis and Statistical Modelling for theIdentification of Metabolomics Biomarkers in 1H-NMR Spectroscopy","authors":"Baptiste Féraud, Réjane Rousseau, P. Tullio, M. Verleysen, B. Govaerts","doi":"10.4172/2155-6180.1000367","DOIUrl":"https://doi.org/10.4172/2155-6180.1000367","url":null,"abstract":"In order to maintain life, living organism’s product and transform small molecules called metabolites. Metabolomics aims at studying the development of biological reactions resulting from a contact with a physio-pathological stimulus, through these metabolites. The 1H-NMR spectroscopy is widely used to graphically describe a metabolite composition via spectra. Biologists can then confirm or invalidate the development of a biological reaction if specific NMR spectral regions are altered from a given physiological situation to another. However, this pro-cess supposes a preliminary identification step which traditionally consists in the study of the two first components of a Principal Component Analysis (PCA). This paper presents a new methodology in two main steps providing knowledge on specific 1H-NMR spectral areas via the identification of biomarkers and via the visualization of the effects caused by some external changes. The first step implies Independent Component Analysis (ICA) in order to decompose the spectral data into statistically independent components or sources of information. The in-dependent (pure or composite) metabolites contained in bio fluids are discovered through the sources, and their quantities through mixing weights. Specific questions related to ICA like the choice of the number of components and their ordering are discussed. The second step consists in a statistical modelling of the ICA mixing weights and introduces statistical hypothesis tests on the parameters of the estimated models, with the objective of selecting sources which present biomarkers (or significantly fluctuating spectral regions). Statistical models are considered here for their adaptability to different possible kinds of data or contexts. A computation of contrasts which can lead to the visualization of changes on spectra caused by changes of the factor of interest is also proposed. This methodology is innovative because multi-factors studies (via the use of mixed models) and statistical confirmations of the factors effects are allowed together.","PeriodicalId":87294,"journal":{"name":"Journal of biometrics & biostatistics","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2017-08-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.4172/2155-6180.1000367","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"48928254","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}
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