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

      Pathways to reduced overnight hospitalizations in older adults: Evaluating 62 physical, behavioral, and psychosocial factors

      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

          As our society ages and healthcare costs escalate, researchers and policymakers urgently seek potentially modifiable predictors of reduced healthcare utilization. We aimed to determine whether changes in 62 candidate predictors were associated with reduced frequency, and duration, of overnight hospitalizations. We used data from 11,374 participants in the Health and Retirement Study—a national sample of adults aged >50 in the United States. Using generalized linear regression models with a lagged exposure-wide approach, we evaluated if changes in 62 predictors over four years (between t 0;2006/2008 and t 1;2010/2012) were associated with subsequent hospitalizations during the two years prior to t 2 (2012–2014 (Cohort A) or 2014–2016 (Cohort B)). After robust covariate-adjustment, we observed that changes in some health behaviors (e.g., those engaging in frequent physical activity had 0.80 the rate of overnight hospital stays (95% CI [0.74, 0.87])), physical health conditions (e.g., those with cancer had 1.57 the rate of overnight hospital stays (95% CI [1.35, 1.82])), and psychosocial factors (e.g., those who helped friends/neighbors/relatives 100–199 hours/year had 0.73 the rate of overnight hospital stays (95% CI [0.63, 0.85])) were associated with subsequent hospitalizations. Findings for both the frequency, and duration, of hospitalizations were mostly similar. Changes in a number of diverse factors were associated with decreased frequency, and duration, of overnight hospitalizations. Notably, some psychosocial factors (e.g., informal helping) had effect sizes equivalent to or larger than some physical health conditions (e.g., diabetes) and health behaviors (e.g., smoking). These psychosocial factors are mostly modifiable and with further research could be novel intervention targets for reducing hospitalizations.

          Related collections

          Most cited references59

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

          Sensitivity Analysis in Observational Research: Introducing the E-Value.

          Sensitivity analysis is useful in assessing how robust an association is to potential unmeasured or uncontrolled confounding. This article introduces a new measure called the "E-value," which is related to the evidence for causality in observational studies that are potentially subject to confounding. The E-value is defined as the minimum strength of association, on the risk ratio scale, that an unmeasured confounder would need to have with both the treatment and the outcome to fully explain away a specific treatment-outcome association, conditional on the measured covariates. A large E-value implies that considerable unmeasured confounding would be needed to explain away an effect estimate. A small E-value implies little unmeasured confounding would be needed to explain away an effect estimate. The authors propose that in all observational studies intended to produce evidence for causality, the E-value be reported or some other sensitivity analysis be used. They suggest calculating the E-value for both the observed association estimate (after adjustments for measured confounders) and the limit of the confidence interval closest to the null. If this were to become standard practice, the ability of the scientific community to assess evidence from observational studies would improve considerably, and ultimately, science would be strengthened.
            Bookmark
            • Record: found
            • Abstract: not found
            • Article: not found

            Multiple Comparisons among Means

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

              Cohort Profile: the Health and Retirement Study (HRS).

              The Health and Retirement Study (HRS) is a nationally representative longitudinal survey of more than 37 000 individuals over age 50 in 23 000 households in the USA. The survey, which has been fielded every 2 years since 1992, was established to provide a national resource for data on the changing health and economic circumstances associated with ageing at both individual and population levels. Its multidisciplinary approach is focused on four broad topics-income and wealth; health, cognition and use of healthcare services; work and retirement; and family connections. HRS data are also linked at the individual level to administrative records from Social Security and Medicare, Veteran's Administration, the National Death Index and employer-provided pension plan information. Since 2006, data collection has expanded to include biomarkers and genetics as well as much greater depth in psychology and social context. This blend of economic, health and psychosocial information provides unprecedented potential to study increasingly complex questions about ageing and retirement. The HRS has been a leading force for rapid release of data while simultaneously protecting the confidentiality of respondents. Three categories of data-public, sensitive and restricted-can be accessed through procedures described on the HRS website (hrsonline.isr.umich.edu).
                Bookmark

                Author and article information

                Contributors
                Role: ConceptualizationRole: Data curationRole: Formal analysisRole: MethodologyRole: Project administrationRole: ResourcesRole: SoftwareRole: ValidationRole: VisualizationRole: Writing – original draftRole: Writing – review & editing
                Role: Writing – original draftRole: Writing – review & editing
                Role: ConceptualizationRole: Formal analysisRole: MethodologyRole: Project administrationRole: ResourcesRole: SoftwareRole: SupervisionRole: ValidationRole: VisualizationRole: Writing – review & editing
                Role: ConceptualizationRole: Data curationRole: Formal analysisRole: Funding acquisitionRole: MethodologyRole: Project administrationRole: ResourcesRole: SoftwareRole: SupervisionRole: ValidationRole: VisualizationRole: Writing – original draftRole: Writing – review & editing
                Role: Editor
                Journal
                PLoS One
                PLoS One
                plos
                PLOS ONE
                Public Library of Science (San Francisco, CA USA )
                1932-6203
                10 November 2022
                2022
                : 17
                : 11
                : e0277222
                Affiliations
                [1 ] Department of Psychology, University of British Columbia, Vancouver, British Columbia, Canada
                [2 ] Human Flourishing Program, Institute for Quantitative Social Science, Harvard University, Cambridge, Massachusetts, United States of America
                [3 ] Department of Biostatistics, Harvard T.H. Chan School of Public Health, Harvard University, Boston, Massachusetts, United States of America
                [4 ] Department of Epidemiology, Harvard T.H. Chan School of Public Health, Harvard University, Boston, Massachusetts, United States of America
                [5 ] Department of Social & Behavioral Sciences, Harvard T.H. Chan School of Public Health, Harvard University, Boston, Massachusetts, United States of America
                [6 ] Lee Kum Sheung Center for Health and Happiness, Harvard T.H. Chan School of Public Health, Harvard University, Boston, Massachusetts, United States of America
                Universitatsklinikum Schleswig Holstein Campus Lubeck, GERMANY
                Author notes

                Competing Interests: I have read the journal’s policy and the authors of this manuscript have the following competing interests: Dr. VanderWeele reports receiving personal fees from Flerish Inc. and Flourishing Metrics. No other disclosures were reported. This does not alter our adherence to PLOS ONE policies on data sharing and materials.

                Author information
                https://orcid.org/0000-0002-6015-4146
                https://orcid.org/0000-0002-1510-8976
                Article
                PONE-D-22-18381
                10.1371/journal.pone.0277222
                9648713
                36355758
                df9327af-1508-45be-b5b0-35f154ddf11d
                © 2022 Nakamura 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
                : 28 June 2022
                : 24 October 2022
                Page count
                Figures: 0, Tables: 4, Pages: 23
                Funding
                Funded by: funder-id http://dx.doi.org/10.13039/501100000245, Michael Smith Foundation for Health Research;
                Award Recipient :
                This work was supported by a grant from the Michael Smith Foundation for Health Research ( https://www.msfhr.org/) awarded to ESK. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
                Categories
                Research Article
                Medicine and Health Sciences
                Health Care
                Health Care Facilities
                Hospitals
                Medicine and Health Sciences
                Public and Occupational Health
                Behavioral and Social Aspects of Health
                People and Places
                Population Groupings
                Age Groups
                Children
                People and Places
                Population Groupings
                Families
                Children
                Medicine and Health Sciences
                Health Care
                Psychological and Psychosocial Issues
                Biology and Life Sciences
                Neuroscience
                Cognitive Science
                Cognitive Neuroscience
                Cognitive Neurology
                Cognitive Impairment
                Biology and Life Sciences
                Neuroscience
                Cognitive Neuroscience
                Cognitive Neurology
                Cognitive Impairment
                Medicine and Health Sciences
                Neurology
                Cognitive Neurology
                Cognitive Impairment
                Social Sciences
                Economics
                Finance
                Medicine and Health Sciences
                Mental Health and Psychiatry
                Medicine and Health Sciences
                Mental Health and Psychiatry
                Mood Disorders
                Depression
                Custom metadata
                The data underlying the results presented in the study are available from The Health and Retirement Study: https://hrs.isr.umich.edu/data-products.

                Uncategorized
                Uncategorized

                Comments

                Comment on this article