Pub Date : 2020-02-28DOI: 10.15406/bbij.2020.09.00296
J. Tallon, Antonio J. Silva, Aldo M. Costa, A. Barros
Introduction: Our paper concern two fundamental pillars to face obesity in adolescence- nutrition education and the phenomenon of human variability, namely in the biological and behavior dimension. Objectives: Assessment of the impact of an innovate school-based nutrition education program (OBESIDATA); the multivariate study of the anthropometric profile and physical activity pattern of adolescents in Portugal; comparison between energy consumption and their energy needs; Evaluation of the accuracy of four commonly used basal metabolic rate prediction equations. Results: After a two weeks period of open interactive digital platform, 85.8% of students increased their nutritional knowledge; the overall prevalence of overweight and obesity in adolescents was 16.5% and 5.9%, respectively; just 38% of participants reported a level of physical activity in line with WHO recommendations; the RMR mean differences of six identified anthropometrics clusters vary from 1349 Kcalories to 1955 Kcalories; the mean reported energy intake was lower than the estimated energy requirements; from all predictive equations estimating energy requirements the relative accuracy, using indirect calorimetric evaluations, is just about 17%. Conclusions: School-based nutrition using technology may provide a practical, attractive and cost- effective strategy to improve nutrition knowledge and eating behaviors; the adolescent’s prevalence of overweight/obesity remains relatively high and physical activity was clear below the WHO recommendations; at average level adolescents REI seems to be lower than their EER, but REI reveals a great individual variability; the accuracy of RMR using predictive equations may have limited applicability; a new paradigma to prevent obesity is coming where genetic will have soon a practical central role.1,2
{"title":"Obesity in adolescence-from etiological variability to interventional efficacy in the school context","authors":"J. Tallon, Antonio J. Silva, Aldo M. Costa, A. Barros","doi":"10.15406/bbij.2020.09.00296","DOIUrl":"https://doi.org/10.15406/bbij.2020.09.00296","url":null,"abstract":"Introduction: Our paper concern two fundamental pillars to face obesity in adolescence- nutrition education and the phenomenon of human variability, namely in the biological and behavior dimension. Objectives: Assessment of the impact of an innovate school-based nutrition education program (OBESIDATA); the multivariate study of the anthropometric profile and physical activity pattern of adolescents in Portugal; comparison between energy consumption and their energy needs; Evaluation of the accuracy of four commonly used basal metabolic rate prediction equations. Results: After a two weeks period of open interactive digital platform, 85.8% of students increased their nutritional knowledge; the overall prevalence of overweight and obesity in adolescents was 16.5% and 5.9%, respectively; just 38% of participants reported a level of physical activity in line with WHO recommendations; the RMR mean differences of six identified anthropometrics clusters vary from 1349 Kcalories to 1955 Kcalories; the mean reported energy intake was lower than the estimated energy requirements; from all predictive equations estimating energy requirements the relative accuracy, using indirect calorimetric evaluations, is just about 17%. Conclusions: School-based nutrition using technology may provide a practical, attractive and cost- effective strategy to improve nutrition knowledge and eating behaviors; the adolescent’s prevalence of overweight/obesity remains relatively high and physical activity was clear below the WHO recommendations; at average level adolescents REI seems to be lower than their EER, but REI reveals a great individual variability; the accuracy of RMR using predictive equations may have limited applicability; a new paradigma to prevent obesity is coming where genetic will have soon a practical central role.1,2","PeriodicalId":90455,"journal":{"name":"Biometrics & biostatistics international journal","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2020-02-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"90317001","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 : 2020-02-11DOI: 10.15406/bbij.2020.09.00294
R. Shanker, Kamlesh Kumar Shukla
A new three-parameter size-biased Poisson-Lindley distribution which includes several one parameter and two-parameter size-biased distributions including size-biased geometric distribution (SBGD), size-biased negative binomial distribution (SBNBD), size-biased Poisson-Lindley distribution (SBPLD), size-biased Poisson-Shanker distribution (SBPSD), size-biased two-parameter Poisson-Lindley distribution-1 (SBTPPLD-1), size-biased two-parameter Poisson-Lindley distribution-2(SBTPPLD-2), size-biased quasi Poisson-Lindley distribution (SBQPLD) and size-biased new quasi Poisson-Lindley distribution (SBNQPLD) for particular cases of parameters has been proposed. Its various statistical properties based on moments including coefficient of variation, skewness, kurtosis and index of dispersion have been studied. Maximum likelihood estimation has been discussed for estimating the parameters of the distribution. Goodness of fit of the proposed distribution has been discussed.
{"title":"A new three-parameter size-biased poisson-lindley distribution with properties and applications","authors":"R. Shanker, Kamlesh Kumar Shukla","doi":"10.15406/bbij.2020.09.00294","DOIUrl":"https://doi.org/10.15406/bbij.2020.09.00294","url":null,"abstract":"A new three-parameter size-biased Poisson-Lindley distribution which includes several one parameter and two-parameter size-biased distributions including size-biased geometric distribution (SBGD), size-biased negative binomial distribution (SBNBD), size-biased Poisson-Lindley distribution (SBPLD), size-biased Poisson-Shanker distribution (SBPSD), size-biased two-parameter Poisson-Lindley distribution-1 (SBTPPLD-1), size-biased two-parameter Poisson-Lindley distribution-2(SBTPPLD-2), size-biased quasi Poisson-Lindley distribution (SBQPLD) and size-biased new quasi Poisson-Lindley distribution (SBNQPLD) for particular cases of parameters has been proposed. Its various statistical properties based on moments including coefficient of variation, skewness, kurtosis and index of dispersion have been studied. Maximum likelihood estimation has been discussed for estimating the parameters of the distribution. Goodness of fit of the proposed distribution has been discussed.","PeriodicalId":90455,"journal":{"name":"Biometrics & biostatistics international journal","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2020-02-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"82711195","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 : 2019-12-30DOI: 10.15406/bbij.2019.08.00293
Dina H. Abdel Hady
{"title":"Parameter estimation for the bivariate inverse lomax distribution by the EM algorithm based on censored samples","authors":"Dina H. Abdel Hady","doi":"10.15406/bbij.2019.08.00293","DOIUrl":"https://doi.org/10.15406/bbij.2019.08.00293","url":null,"abstract":"","PeriodicalId":90455,"journal":{"name":"Biometrics & biostatistics international journal","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2019-12-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"80017175","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 : 2019-12-26DOI: 10.15406/bbij.2019.08.00292
Dr. C.R. Subudhi, N. Jena, S. Suryavanshi, R. Subudhi
This study was under taken in the U.G. thesis work in the Dept. Of SWCE, CAET, OUAT, Bhubaneswar during the year 2018-19 . Sambalpur district has a geographical area of 6702 sq.km. Sambalpur district has latitude of 21° 28’ 5.4660’’ N and longitude of 83° 58’ 31.4508’’ E. The average rainfall at Sambalpur district is around 1377.9 mm, though it receives high amount rainfall but most of the rainfall occurred during kharif . So most of the crops get low yield due to improper crop planning. Thus, this study is proposed to be undertaken with the following objective: Probability analysis of annual, seasonal and monthly rainfall data of Sambalpur district. So rainfall data were collected from OUAT, Agril Meteorology Dept. from 2001 to 2017(17 years) monthly, seasonal and annual rainfall were analyzed .Probability analysis have been made and equations were fitted to different distributions and best fitted equations were tested. Monthly, Annual and seasonal probability analysis of rainfall data shows the probability rainfall distribution of Sambalpur district in different months, years and seasons. It is observed that rainfall during June to Sep is slightly less than 1000 mm and cropping pattern like paddy(110 days) may be followed by mustard is suitable to this region. Also if the kharif rain can be harvested and it can be reused for another rabi crop by using sprinkler or drip irrigation, which will give benefit to the farmers. Annual rainfall of Sambalpur district is 1377.9 mm at 50% probability level.
{"title":"Rainfall probability analysis for crop planning in Sambalpur district of Odisha, India","authors":"Dr. C.R. Subudhi, N. Jena, S. Suryavanshi, R. Subudhi","doi":"10.15406/bbij.2019.08.00292","DOIUrl":"https://doi.org/10.15406/bbij.2019.08.00292","url":null,"abstract":"This study was under taken in the U.G. thesis work in the Dept. Of SWCE, CAET, OUAT, Bhubaneswar during the year 2018-19 . Sambalpur district has a geographical area of 6702 sq.km. Sambalpur district has latitude of 21° 28’ 5.4660’’ N and longitude of 83° 58’ 31.4508’’ E. The average rainfall at Sambalpur district is around 1377.9 mm, though it receives high amount rainfall but most of the rainfall occurred during kharif . So most of the crops get low yield due to improper crop planning. Thus, this study is proposed to be undertaken with the following objective: Probability analysis of annual, seasonal and monthly rainfall data of Sambalpur district. So rainfall data were collected from OUAT, Agril Meteorology Dept. from 2001 to 2017(17 years) monthly, seasonal and annual rainfall were analyzed .Probability analysis have been made and equations were fitted to different distributions and best fitted equations were tested. Monthly, Annual and seasonal probability analysis of rainfall data shows the probability rainfall distribution of Sambalpur district in different months, years and seasons. It is observed that rainfall during June to Sep is slightly less than 1000 mm and cropping pattern like paddy(110 days) may be followed by mustard is suitable to this region. Also if the kharif rain can be harvested and it can be reused for another rabi crop by using sprinkler or drip irrigation, which will give benefit to the farmers. Annual rainfall of Sambalpur district is 1377.9 mm at 50% probability level.","PeriodicalId":90455,"journal":{"name":"Biometrics & biostatistics international journal","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2019-12-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"80479732","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 : 2019-12-05DOI: 10.15406/bbij.2019.08.00289
Falgore Jamilu Yunusa, Doguwa Sani Ibrahim, I. Audu
{"title":"The Weibull-Inverse Lomax (WIL) distribution with Application on Bladder Cancer","authors":"Falgore Jamilu Yunusa, Doguwa Sani Ibrahim, I. Audu","doi":"10.15406/bbij.2019.08.00289","DOIUrl":"https://doi.org/10.15406/bbij.2019.08.00289","url":null,"abstract":"","PeriodicalId":90455,"journal":{"name":"Biometrics & biostatistics international journal","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2019-12-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"86574055","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 : 2019-11-25DOI: 10.15406/bbij.2019.08.00288
J. Tallon, Saavedra Dias, R, António J. Silva, A. Barros, Aldo M. Costa
Adolescence refers to the period of the transition from childhood into adulthood.1 Historically, it has been defined as being between the ages of 12 and 18 years of age, which approximately corresponds to the time of puberty onset to guardian independence.1 A recent work by some leading scholars has proposed that an expanded definition and timeframe of 10 to 24 years of age corresponds more closely to adolescent growth and general knowledge of this life period.2
{"title":"Characterization of the anthropometric profile and physical activity levels of Portuguese adolescents","authors":"J. Tallon, Saavedra Dias, R, António J. Silva, A. Barros, Aldo M. Costa","doi":"10.15406/bbij.2019.08.00288","DOIUrl":"https://doi.org/10.15406/bbij.2019.08.00288","url":null,"abstract":"Adolescence refers to the period of the transition from childhood into adulthood.1 Historically, it has been defined as being between the ages of 12 and 18 years of age, which approximately corresponds to the time of puberty onset to guardian independence.1 A recent work by some leading scholars has proposed that an expanded definition and timeframe of 10 to 24 years of age corresponds more closely to adolescent growth and general knowledge of this life period.2","PeriodicalId":90455,"journal":{"name":"Biometrics & biostatistics international journal","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2019-11-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"88693695","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 : 2019-11-21DOI: 10.15406/bbij.2019.08.00286
M. Jose
By mental illness, we mean a medical condition, which disturbs a person’s intellectual and psychic capacities and ability to have normal relation with others. It may affect daily functioning of the person.1 Social inequalities result in increased risk of many common mental disorders. Psychiatric disorders differ in their nature, severity, and prevalence. Common causes of Mental Disorders are communities and cultures, relationships, environmental factors, structure of the brain, biological factors, drug intakes etc.2
{"title":"Statistical analysis of social determinants of mental health problems","authors":"M. Jose","doi":"10.15406/bbij.2019.08.00286","DOIUrl":"https://doi.org/10.15406/bbij.2019.08.00286","url":null,"abstract":"By mental illness, we mean a medical condition, which disturbs a person’s intellectual and psychic capacities and ability to have normal relation with others. It may affect daily functioning of the person.1 Social inequalities result in increased risk of many common mental disorders. Psychiatric disorders differ in their nature, severity, and prevalence. Common causes of Mental Disorders are communities and cultures, relationships, environmental factors, structure of the brain, biological factors, drug intakes etc.2","PeriodicalId":90455,"journal":{"name":"Biometrics & biostatistics international journal","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2019-11-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"82432700","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 : 2019-11-21DOI: 10.15406/bbij.2019.08.00287
C. Subudhi, N. Jena, S. Suryavanshi, R. Subudhi
{"title":"Rainfall probability analysis for crop planning in Bargarh district of Odisha, India","authors":"C. Subudhi, N. Jena, S. Suryavanshi, R. Subudhi","doi":"10.15406/bbij.2019.08.00287","DOIUrl":"https://doi.org/10.15406/bbij.2019.08.00287","url":null,"abstract":"","PeriodicalId":90455,"journal":{"name":"Biometrics & biostatistics international journal","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2019-11-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"83061445","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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