2
views
0
recommends
+1 Recommend
0 collections
    0
    shares
      • Record: found
      • Abstract: found
      • Article: found
      Is Open Access

      Causal relations of health indices inferred statistically using the DirectLiNGAM algorithm from big data of Osaka prefecture health checkups

      research-article

      Read this article at

      Bookmark
          There is no author summary for this article yet. Authors can add summaries to their articles on ScienceOpen to make them more accessible to a non-specialist audience.

          Abstract

          Causal relations among many statistical variables have been assessed using a Linear non-Gaussian Acyclic Model (LiNGAM). Using access to large amounts of health checkup data from Osaka prefecture obtained during the six fiscal years of years 2012–2017, we applied the DirectLiNGAM algorithm as a trial to extract causal relations among health indices for age groups and genders. Results show that LiNGAM yields interesting and reasonable results, suggesting causal relations and correlation among the statistical indices used for these analyses.

          Related collections

          Most cited references15

          • Record: found
          • Abstract: not found
          • Article: not found

          On Information and Sufficiency

            Bookmark
            • Record: found
            • Abstract: found
            • Article: found
            Is Open Access

            The Global Epidemic of the Metabolic Syndrome

            Metabolic syndrome, variously known also as syndrome X, insulin resistance, etc., is defined by WHO as a pathologic condition characterized by abdominal obesity, insulin resistance, hypertension, and hyperlipidemia. Though there is some variation in the definition by other health care organization, the differences are minor. With the successful conquest of communicable infectious diseases in most of the world, this new non-communicable disease (NCD) has become the major health hazard of modern world. Though it started in the Western world, with the spread of the Western lifestyle across the globe, it has become now a truly global problem. The prevalence of the metabolic syndrome is often more in the urban population of some developing countries than in its Western counterparts. The two basic forces spreading this malady are the increase in consumption of high calorie-low fiber fast food and the decrease in physical activity due to mechanized transportations and sedentary form of leisure time activities. The syndrome feeds into the spread of the diseases like type 2 diabetes, coronary diseases, stroke, and other disabilities. The total cost of the malady including the cost of health care and loss of potential economic activity is in trillions. The present trend is not sustainable unless a magic cure is found (unlikely) or concerted global/governmental/societal efforts are made to change the lifestyle that is promoting it. There are certainly some elements in the causation of the metabolic syndrome that cannot be changed but many are amenable for corrections and curtailments. For example, better urban planning to encourage active lifestyle, subsidizing consumption of whole grains and possible taxing high calorie snacks, restricting media advertisement of unhealthy food, etc. Revitalizing old fashion healthier lifestyle, promoting old-fashioned foods using healthy herbs rather than oil and sugar, and educating people about choosing healthy/wholesome food over junks are among the steps that can be considered.
              Bookmark
              • Record: found
              • Abstract: found
              • Article: not found

              Metabolic syndrome: pathophysiology, management, and modulation by natural compounds

              Metabolic syndrome (MetS) represents a cluster of metabolic abnormalities that include hypertension, central obesity, insulin resistance, and atherogenic dyslipidemia, and is strongly associated with an increased risk for developing diabetes and atherosclerotic and nonatherosclerotic cardiovascular disease (CVD). The pathogenesis of MetS involves both genetic and acquired factors that contribute to the final pathway of inflammation that leads to CVD. MetS has gained significant importance recently due to the exponential increase in obesity worldwide. Early diagnosis is important in order to employ lifestyle and risk factor modification. Here, we review the epidemiology and pathogenesis of MetS, the role of inflammation in MetS, and summarize existing natural therapies for MetS.
                Bookmark

                Author and article information

                Contributors
                Role: ConceptualizationRole: Data curationRole: Formal analysisRole: Funding acquisitionRole: InvestigationRole: MethodologyRole: Project administrationRole: SupervisionRole: ValidationRole: Writing – original draftRole: Writing – review & editing
                Role: InvestigationRole: SoftwareRole: Writing – review & editing
                Role: Data curationRole: Formal analysisRole: Investigation
                Role: ConceptualizationRole: Project administrationRole: SupervisionRole: ValidationRole: Writing – original draftRole: Writing – review & editing
                Role: Data curation
                Role: ConceptualizationRole: InvestigationRole: MethodologyRole: ValidationRole: Writing – original draftRole: Writing – review & editing
                Role: Validation
                Role: Validation
                Role: Validation
                Role: Validation
                Role: Funding acquisitionRole: Supervision
                Role: Editor
                Journal
                PLoS One
                PLoS One
                plos
                plosone
                PLoS ONE
                Public Library of Science (San Francisco, CA USA )
                1932-6203
                2020
                23 December 2020
                : 15
                : 12
                : e0243229
                Affiliations
                [1 ] Graduate School of Medical Care and Technology, Teikyo University, Tokyo, Japan
                [2 ] Health Care Division, Health and Counseling Center, Osaka University, Osaka, Japan
                [3 ] Research Center for Nuclear Physics, Osaka University, Osaka, Japan
                [4 ] Graduate School of Biomedical Sciences, Tokushima University, Tokushima, Japan
                [5 ] Department of Nephrology, Graduate School of Medicine, Osaka University, Osaka, Japan
                [6 ] Division of Health Sciences, Graduate School of Medicine, Osaka University, Osaka, Japan
                [7 ] Department of Medical Informatics, Wakayama Medical University Hospital, Wakayama, Japan
                University of Missouri, UNITED STATES
                Author notes

                Competing Interests: The authors have declared that no competing interests exist.

                Author information
                https://orcid.org/0000-0002-5233-6003
                Article
                PONE-D-20-14743
                10.1371/journal.pone.0243229
                7757823
                33362207
                1bbe84f2-3f34-4c63-bb5d-09042254d4fa
                © 2020 Kotoku et al

                This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

                History
                : 17 May 2020
                : 17 November 2020
                Page count
                Figures: 9, Tables: 5, Pages: 19
                Funding
                Funded by: funder-id http://dx.doi.org/10.13039/501100001691, Japan Society for the Promotion of Science;
                Award ID: 18K07646
                Award Recipient :
                Funded by: funder-id http://dx.doi.org/10.13039/501100001691, Japan Society for the Promotion of Science;
                Award ID: 19H03871
                Award Recipient :
                This project was supported by the Ministry of Health, Labour and Welfare. This work was partly supported by Japan Society for the Promotion of Science (JSPS, https://www.jsps.go.jp/english/index.html) KAKENHI Grants (Nos. 18K07646 to JK and 19H03871 to TM). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
                Categories
                Research Article
                People and Places
                Population Groupings
                Age Groups
                Physical Sciences
                Mathematics
                Probability Theory
                Probability Distribution
                Physical Sciences
                Mathematics
                Probability Theory
                Statistical Distributions
                Physical Sciences
                Mathematics
                Statistics
                Statistical Data
                Physical Sciences
                Mathematics
                Applied Mathematics
                Algorithms
                Machine Learning Algorithms
                Research and Analysis Methods
                Simulation and Modeling
                Algorithms
                Machine Learning Algorithms
                Computer and Information Sciences
                Artificial Intelligence
                Machine Learning
                Machine Learning Algorithms
                Physical Sciences
                Chemistry
                Chemical Compounds
                Organic Compounds
                Carbohydrates
                Monosaccharides
                Glucose
                Physical Sciences
                Chemistry
                Organic Chemistry
                Organic Compounds
                Carbohydrates
                Monosaccharides
                Glucose
                Physical Sciences
                Physics
                Thermodynamics
                Entropy
                Physical Sciences
                Mathematics
                Applied Mathematics
                Algorithms
                Research and Analysis Methods
                Simulation and Modeling
                Algorithms
                Custom metadata
                Data cannot be shared publicly because local governments own medical check-up data. Data are available from the Health and Counseling Center, Osaka University (contact via campuslifekenkou-syomu@ 123456hacc.osaka-u.ac.jp ) for researchers who meet the criteria for access to confidential data.

                Uncategorized
                Uncategorized

                Comments

                Comment on this article