In medical research, analyzing the time it takes for a phenomenon to occur is sometimes crucial. However, various factors can contribute to the length of survival or observation periods, and removing specific data can lead to bias results. In this paper, we discuss the Kaplan-Meier analysis and Cox proportional hazards regression model, which are the most frequently used methods in survival analysis. For the first step, we shall discuss the temporal concepts needed in survival analysis, such as cohort studies and then the basic statistical functions dealt with in survival analysis. After solidifying the concepts, methods of understanding and practical application of the Kaplan-Meier survival analysis is noted. After that, we will discuss the analysis methods for the Cox proportional hazards regression model, which includes multiple covariates. With the interpretation method of Cox proportional hazards regression result, we then discuss methods for checking the assumptions of the Cox proportional hazards regression, such as log minus log plots. Finally, we briefly explain the concept of time-dependent regression analysis. It is our aim that through this paper, readers can obtain an understanding on survival analysis and learn how to perform it.
{"title":"Kaplan-Meier and Cox proportional hazards regression in survival\u0000 analysis: statistical standard and guideline of Life Cycle\u0000 Committee","authors":"S. Lee","doi":"10.54724/lc.2023.e8","DOIUrl":"https://doi.org/10.54724/lc.2023.e8","url":null,"abstract":"In medical research, analyzing the time it takes for a phenomenon to occur is sometimes crucial. However, various factors can contribute to the length of survival or observation periods, and removing specific data can lead to bias results. In this paper, we discuss the Kaplan-Meier analysis and Cox proportional hazards regression model, which are the most frequently used methods in survival analysis. For the first step, we shall discuss the temporal concepts needed in survival analysis, such as cohort studies and then the basic statistical functions dealt with in survival analysis. After solidifying the concepts, methods of understanding and practical application of the Kaplan-Meier survival analysis is noted. After that, we will discuss the analysis methods for the Cox proportional hazards regression model, which includes multiple covariates. With the interpretation method of Cox proportional hazards regression result, we then discuss methods for checking the assumptions of the Cox proportional hazards regression, such as log minus log plots. Finally, we briefly explain the concept of time-dependent regression analysis. It is our aim that through this paper, readers can obtain an understanding on survival analysis and learn how to perform it.","PeriodicalId":54952,"journal":{"name":"International Journal of Life Cycle Assessment","volume":"52 1","pages":""},"PeriodicalIF":4.8,"publicationDate":"2023-05-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"79313892","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-05-16DOI: 10.1007/s11367-023-02163-z
Javiera García-Leal, Andrea Teresa Espinoza Pérez, Óscar C. Vásquez
{"title":"Sustainable diets optimal design for the massive food services: economic versus environmental aspects","authors":"Javiera García-Leal, Andrea Teresa Espinoza Pérez, Óscar C. Vásquez","doi":"10.1007/s11367-023-02163-z","DOIUrl":"https://doi.org/10.1007/s11367-023-02163-z","url":null,"abstract":"","PeriodicalId":54952,"journal":{"name":"International Journal of Life Cycle Assessment","volume":"1 1","pages":"1-14"},"PeriodicalIF":4.8,"publicationDate":"2023-05-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44223076","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-05-15DOI: 10.1007/s11367-023-02169-7
E. Sanyé‐Mengual, F. Biganzoli, A. Valente, S. Pfister, Serenella Sala
{"title":"What are the main environmental impacts and products contributing to the biodiversity footprint of EU consumption? A comparison of life cycle impact assessment methods and models","authors":"E. Sanyé‐Mengual, F. Biganzoli, A. Valente, S. Pfister, Serenella Sala","doi":"10.1007/s11367-023-02169-7","DOIUrl":"https://doi.org/10.1007/s11367-023-02169-7","url":null,"abstract":"","PeriodicalId":54952,"journal":{"name":"International Journal of Life Cycle Assessment","volume":"1 1","pages":"1-17"},"PeriodicalIF":4.8,"publicationDate":"2023-05-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"45318283","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-05-15DOI: 10.1007/s11367-023-02180-y
Johanna Suikkanen, Susanna Horn, Jáchym Judl, D. Lazarevic, J. Niemistö
{"title":"Factors contributing to the relevance and continuity of life cycle assessment networks","authors":"Johanna Suikkanen, Susanna Horn, Jáchym Judl, D. Lazarevic, J. Niemistö","doi":"10.1007/s11367-023-02180-y","DOIUrl":"https://doi.org/10.1007/s11367-023-02180-y","url":null,"abstract":"","PeriodicalId":54952,"journal":{"name":"International Journal of Life Cycle Assessment","volume":"1 1","pages":"1-12"},"PeriodicalIF":4.8,"publicationDate":"2023-05-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42821398","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Yejoon Kim, Wongi Woo, Vincent Kipkorir, Masoud Rahmati, Ai Koyanagi, Jae Il Shin, Lee Smith
Objective: The few existing country-specific studies on vaccine hesitancy in Africa are limited by their focus on specific population groups such as health care workers or medical students. Thus, we aimed to provide a comparative systematic review and meta-analysis of COVID-19 vaccine acceptance rates in African countries and their predictors. Methods: Fifteen studies on COVID-19 vaccine acceptance rates in African countries were reviewed in the PubMed/MEDLINE, Embase, and Google Scholar. Meta-analysis investigated the summary effect and inter-study heterogeneity of vaccine acceptance rates and influential factors. Results: Overall, the COVID-19 vaccine acceptance rate was 71.0% (95% CI 64.0 to 77.0). However, as time passed, the vaccine acceptance rate showed a decrease (second half of 2020: 81%, first half of 2021: 67%). Also, the vaccine acceptance rates in urban areas were higher than in rural areas (urban: 82%, rural: 72%). When considering region, vaccine acceptance rates in Eastern and Southern African countries were higher than in Western and North African countries (East: 72%, South: 72%, West: 60%, and North: 52%). Finally, factors such as older age, male sex, and wealth were identified as factors associated with a more acceptive attitude toward vaccination. Conclusion: COVID-19 vaccine acceptance rates demonstrated shifts and was affected by several factors. The rates decreased over time, were lower in rural (vs. urban) settings, and were relatively low in Northern and West African countries (vs. Southern and East African countries). We also found differences in vaccine acceptance rates by some socio-demographic characteristics. Targeting these characteristics, devising strategies to improve vaccine uptake in Africa could help improve vaccination rates.
{"title":"Shifts in COVID-19 vaccine acceptance rates among African countries: A systematic review and meta-analysis","authors":"Yejoon Kim, Wongi Woo, Vincent Kipkorir, Masoud Rahmati, Ai Koyanagi, Jae Il Shin, Lee Smith","doi":"10.54724/lc.2023.e7","DOIUrl":"https://doi.org/10.54724/lc.2023.e7","url":null,"abstract":"Objective: The few existing country-specific studies on vaccine hesitancy in Africa are limited by their focus on specific population groups such as health care workers or medical students. Thus, we aimed to provide a comparative systematic review and meta-analysis of COVID-19 vaccine acceptance rates in African countries and their predictors. Methods: Fifteen studies on COVID-19 vaccine acceptance rates in African countries were reviewed in the PubMed/MEDLINE, Embase, and Google Scholar. Meta-analysis investigated the summary effect and inter-study heterogeneity of vaccine acceptance rates and influential factors. Results: Overall, the COVID-19 vaccine acceptance rate was 71.0% (95% CI 64.0 to 77.0). However, as time passed, the vaccine acceptance rate showed a decrease (second half of 2020: 81%, first half of 2021: 67%). Also, the vaccine acceptance rates in urban areas were higher than in rural areas (urban: 82%, rural: 72%). When considering region, vaccine acceptance rates in Eastern and Southern African countries were higher than in Western and North African countries (East: 72%, South: 72%, West: 60%, and North: 52%). Finally, factors such as older age, male sex, and wealth were identified as factors associated with a more acceptive attitude toward vaccination. Conclusion: COVID-19 vaccine acceptance rates demonstrated shifts and was affected by several factors. The rates decreased over time, were lower in rural (vs. urban) settings, and were relatively low in Northern and West African countries (vs. Southern and East African countries). We also found differences in vaccine acceptance rates by some socio-demographic characteristics. Targeting these characteristics, devising strategies to improve vaccine uptake in Africa could help improve vaccination rates.","PeriodicalId":54952,"journal":{"name":"International Journal of Life Cycle Assessment","volume":"17 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-05-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135673516","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-05-10DOI: 10.21203/rs.3.rs-1998674/v1
Yejoo Kim, W. Woo, V. Kipkorir, M. Rahmati, A. Koyanagi, J. Shin, Lee Smith
Objective: To provide a comparative systematic review and meta-analysis of COVID-19 vaccine acceptance rates in African countries and their predictors. Methods: : Fifteen studies on COVID-19 vaccine acceptance rate s in African countries were reviewed in the Medline database via PubMed. Meta-analysis investigated the summary effect and inter-study heterogeneity of vaccine acceptance rates and influential factors. Results: : Overall, the COVID-19 vaccine acceptance rate was 71% (95% CI 64-77). As time passed, the vaccine acceptance rate decreased (second half of 2020: 81%, first half of 2021: 67%). Also, the vaccine acceptance rates in urban areas were higher than in rural areas (urban: 82%, rural: 72%). When considering region, vaccine acceptance rates in Eastern and Southern African countries were higher than in Western and North African countries (East: 72%, South: 72%, West: 60%, North: 52%). Finally, factors such as older age, male sex, and wealth were identified as factors associated with a more acceptive attitude toward vaccination. Conclusions: : COVID-19 vaccine acceptance rates demonstrated shifts and was affected by several factors. The rates decreased over time, were lower in rural (vs. urban) settings, and were relatively low in Northern and West African countries (vs. Southern and East African countries). We also found differences in vaccine acceptance rates by some socio-demographic characteristics. Targeting these characteristics, devising strategies to improve vaccine uptake in Africa could help improve vaccination rates.
目的:对非洲国家COVID-19疫苗接受率及其预测因素进行比较系统回顾和荟萃分析。方法:通过PubMed对Medline数据库中15项非洲国家COVID-19疫苗接受率的研究进行综述。meta分析调查了疫苗接受率和影响因素的总体效应和研究间异质性。结果:总体而言，COVID-19疫苗合格率为71% (95% CI 64-77)。随着时间的推移，疫苗接种率下降(2020年下半年:81%，2021年上半年:67%)。此外，城市地区的疫苗接种率高于农村地区(城市:82%，农村:72%)。在考虑区域时，东部和南部非洲国家的疫苗接受率高于西部和北非国家(东部:72%，南部:72%，西部:60%，北部:52%)。最后，年龄较大、男性和财富等因素被确定为对疫苗接种更接受态度的相关因素。结论:COVID-19疫苗接种率存在变化，并受多种因素影响。随着时间的推移，发病率下降，农村(与城市相比)发病率较低，北非和西非国家(与南部和东非国家相比)发病率相对较低。我们还发现一些社会人口统计学特征在疫苗接受率方面存在差异。针对这些特点，制定战略以提高非洲的疫苗接种率，可能有助于提高疫苗接种率。
{"title":"Shifts in COVID-19 vaccine acceptance rates among African countries:\u0000 A systematic review and meta-analysis","authors":"Yejoo Kim, W. Woo, V. Kipkorir, M. Rahmati, A. Koyanagi, J. Shin, Lee Smith","doi":"10.21203/rs.3.rs-1998674/v1","DOIUrl":"https://doi.org/10.21203/rs.3.rs-1998674/v1","url":null,"abstract":"Objective: To provide a comparative systematic review and meta-analysis of COVID-19 vaccine acceptance rates in African countries and their predictors. Methods: : Fifteen studies on COVID-19 vaccine acceptance rate s in African countries were reviewed in the Medline database via PubMed. Meta-analysis investigated the summary effect and inter-study heterogeneity of vaccine acceptance rates and influential factors. Results: : Overall, the COVID-19 vaccine acceptance rate was 71% (95% CI 64-77). As time passed, the vaccine acceptance rate decreased (second half of 2020: 81%, first half of 2021: 67%). Also, the vaccine acceptance rates in urban areas were higher than in rural areas (urban: 82%, rural: 72%). When considering region, vaccine acceptance rates in Eastern and Southern African countries were higher than in Western and North African countries (East: 72%, South: 72%, West: 60%, North: 52%). Finally, factors such as older age, male sex, and wealth were identified as factors associated with a more acceptive attitude toward vaccination. Conclusions: : COVID-19 vaccine acceptance rates demonstrated shifts and was affected by several factors. The rates decreased over time, were lower in rural (vs. urban) settings, and were relatively low in Northern and West African countries (vs. Southern and East African countries). We also found differences in vaccine acceptance rates by some socio-demographic characteristics. Targeting these characteristics, devising strategies to improve vaccine uptake in Africa could help improve vaccination rates.","PeriodicalId":54952,"journal":{"name":"International Journal of Life Cycle Assessment","volume":"20 1","pages":""},"PeriodicalIF":4.8,"publicationDate":"2023-05-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"89257299","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-05-09DOI: 10.1007/s11367-023-02156-y
Poonam Sutar, Ramdas S. Kadam, G. Yadav
{"title":"Process simulation-based life cycle assessment of the six-step Cu-Cl Cycle of green hydrogen generation and comparative analysis with other Cu-Cl cycles","authors":"Poonam Sutar, Ramdas S. Kadam, G. Yadav","doi":"10.1007/s11367-023-02156-y","DOIUrl":"https://doi.org/10.1007/s11367-023-02156-y","url":null,"abstract":"","PeriodicalId":54952,"journal":{"name":"International Journal of Life Cycle Assessment","volume":" ","pages":"1-18"},"PeriodicalIF":4.8,"publicationDate":"2023-05-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"45031889","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-05-03DOI: 10.1007/s11367-023-02168-8
D. Egas, S. Azarkamand, C. Casals, S. Ponsá, L. Llenas, J. Colón
{"title":"Life cycle assessment of bio-based fertilizers production systems: where are we and where should we be heading?","authors":"D. Egas, S. Azarkamand, C. Casals, S. Ponsá, L. Llenas, J. Colón","doi":"10.1007/s11367-023-02168-8","DOIUrl":"https://doi.org/10.1007/s11367-023-02168-8","url":null,"abstract":"","PeriodicalId":54952,"journal":{"name":"International Journal of Life Cycle Assessment","volume":" ","pages":"1-25"},"PeriodicalIF":4.8,"publicationDate":"2023-05-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44294385","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-05-02DOI: 10.1007/s11367-023-02171-z
Bianca Maria Tragnone, Ioannis Arzoumanidis, Manuela D’Eusanio, L. Petti
{"title":"Contribution of the Product Social Impact Life Cycle Assessment (PSILCA) database in assessing the risks and opportunities of a jar of honey production","authors":"Bianca Maria Tragnone, Ioannis Arzoumanidis, Manuela D’Eusanio, L. Petti","doi":"10.1007/s11367-023-02171-z","DOIUrl":"https://doi.org/10.1007/s11367-023-02171-z","url":null,"abstract":"","PeriodicalId":54952,"journal":{"name":"International Journal of Life Cycle Assessment","volume":"1 1","pages":"1-18"},"PeriodicalIF":4.8,"publicationDate":"2023-05-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43123545","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-05-02DOI: 10.1007/s11367-023-02162-0
Noémie Leroy-Parmentier, S. Valdivia, P. Loubet, G. Sonnemann
{"title":"Alignment of the life cycle initiative’s “principles for the application of life cycle sustainability assessment” with the LCSA practice: A case study review","authors":"Noémie Leroy-Parmentier, S. Valdivia, P. Loubet, G. Sonnemann","doi":"10.1007/s11367-023-02162-0","DOIUrl":"https://doi.org/10.1007/s11367-023-02162-0","url":null,"abstract":"","PeriodicalId":54952,"journal":{"name":"International Journal of Life Cycle Assessment","volume":"1 1","pages":"1-37"},"PeriodicalIF":4.8,"publicationDate":"2023-05-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42076763","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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