{"title":"Dataset of obesity in relation to female-specific cancers in middle eastern countries, 1990 to 2016.","authors":"Mojtaba Daneshvar","doi":"10.1186/s13104-025-07187-2","DOIUrl":null,"url":null,"abstract":"<p><strong>Objectives: </strong>Understanding the relationship between obesity and female-specific cancers (FSCs) is crucial for public health planning and policy development. The current data paper presented a dataset that includes obesity prevalence and incidence rates of breast, ovarian, cervical, and uterine cancers among women in Middle Eastern countries. This dataset could be used for time-trend analysis and different forecasting models. Moreover, exploring the relationship between obesity and FSCs is important to develop preventive healthcare services, especially among developing countries.</p><p><strong>Data description: </strong>The dataset comprises official statistics obtained from reputable sources including the world bank and global burden of disease (GBD) database. The data include a total of 405 observations across 15 middle-eastern countries, from 1990 to 2016. Key variables are obesity prevalence and incidence rate of four major cancers in women including breast cancer, ovarian cancer, cervical cancer, and uterine cancer. This panel data is mainly prepared to investigate the temporal relationship between obesity prevalence and FSC incidence rates, and also performing Counterfactual analysis. Moreover, this data could be utilized for advanced machine learning techniques to estimate future shifts in trend and patterns over time.</p>","PeriodicalId":9234,"journal":{"name":"BMC Research Notes","volume":"18 1","pages":"124"},"PeriodicalIF":1.6000,"publicationDate":"2025-03-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11934536/pdf/","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"BMC Research Notes","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1186/s13104-025-07187-2","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"MULTIDISCIPLINARY SCIENCES","Score":null,"Total":0}
引用次数: 0
Abstract
Objectives: Understanding the relationship between obesity and female-specific cancers (FSCs) is crucial for public health planning and policy development. The current data paper presented a dataset that includes obesity prevalence and incidence rates of breast, ovarian, cervical, and uterine cancers among women in Middle Eastern countries. This dataset could be used for time-trend analysis and different forecasting models. Moreover, exploring the relationship between obesity and FSCs is important to develop preventive healthcare services, especially among developing countries.
Data description: The dataset comprises official statistics obtained from reputable sources including the world bank and global burden of disease (GBD) database. The data include a total of 405 observations across 15 middle-eastern countries, from 1990 to 2016. Key variables are obesity prevalence and incidence rate of four major cancers in women including breast cancer, ovarian cancer, cervical cancer, and uterine cancer. This panel data is mainly prepared to investigate the temporal relationship between obesity prevalence and FSC incidence rates, and also performing Counterfactual analysis. Moreover, this data could be utilized for advanced machine learning techniques to estimate future shifts in trend and patterns over time.
BMC Research NotesBiochemistry, Genetics and Molecular Biology-Biochemistry, Genetics and Molecular Biology (all)
CiteScore
3.60
自引率
0.00%
发文量
363
审稿时长
15 weeks
期刊介绍:
BMC Research Notes publishes scientifically valid research outputs that cannot be considered as full research or methodology articles. We support the research community across all scientific and clinical disciplines by providing an open access forum for sharing data and useful information; this includes, but is not limited to, updates to previous work, additions to established methods, short publications, null results, research proposals and data management plans.