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      Associations Between Satisfaction With Aging and Health and Well-being Outcomes Among Older US Adults

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          Key Points

          Question

          Is aging satisfaction (one’s beliefs about their own aging) associated with physical, behavioral, and psychosocial outcomes?

          Findings

          In this nationwide cohort study of US adults older than 50 years, being in the highest (vs lowest) quartile of aging satisfaction was associated with improvements in some health behaviors (eg, increased likelihood of engaging in frequent physical activity), physical health conditions (eg, reduced risk of mortality), and psychosocial well-being factors (eg, reduced risk of depression) 4 years later, conditional on prebaseline aging satisfaction.

          Meaning

          This study suggests that higher aging satisfaction is associated with improved subsequent health and well-being and highlights potential outcomes if scalable aging satisfaction interventions were developed and deployed at scale.

          Abstract

          Importance

          Researchers and policy makers are expanding the focus from risk factors of disease to seek potentially modifiable health factors that enhance people’s health and well-being. Understanding if and to what degree aging satisfaction (one’s beliefs about their own aging) is associated with a range of health and well-being outcomes aligns with the interests of older adults, researchers, health systems, and politicians.

          Objectives

          To evaluate associations between changes in aging satisfaction and 35 subsequent health and well-being outcomes.

          Design, Setting, and Participants

          This cohort study used data from the Health and Retirement Study, a national, diverse, and longitudinal sample of 13 752 US adults older than 50 years, to evaluate if changes in aging satisfaction (between combined cohorts from 2008 and 2010 and 4 years later, in 2012 and 2014) were subsequently associated with 35 indicators of physical, behavioral, and psychosocial health and well-being in 2016 and 2018. Statistical analysis was conducted from July 24, 2020, to November 6, 2021.

          Exposure

          Aging satisfaction.

          Main Outcomes and Measures

          A total of 35 physical (eg, stroke), behavioral (eg, sleep problems), and psychosocial (eg, depression) outcomes were evaluated using multiple linear and generalized linear regression models. Data from all participants, irrespective of how their levels of aging satisfaction changed from the prebaseline to baseline waves, were incorporated into the overall estimate, which was conditional on prior satisfaction.

          Results

          During the 4-year follow-up period, participants (N = 13 752; 8120 women [59%]; mean [SD] age, 65 [10] years; median age, 64 years [IQR, 56-72 years]; 7507 of 11 824 married [64%]) in the highest (vs lowest) quartile of aging satisfaction had improved physical health (eg, 43% reduced risk of mortality [risk ratio, 0.57; 95% CI, 0.46-0.71]), better health behaviors (eg, 23% increased likelihood of frequent physical activity [risk ratio, 1.23; 95% CI, 1.12-1.34]), and improved psychosocial well-being (eg, higher positive affect [β = 0.51; 95% CI, 0.44-0.58] and lower loneliness [β = −0.41; 95% CI, −0.48 to −0.33]), conditional on prebaseline aging satisfaction.

          Conclusions and Relevance

          This study suggests that higher aging satisfaction is associated with improved subsequent health and well-being. These findings highlight potential outcomes if scalable aging satisfaction interventions were developed and deployed at scale; they also inform the efforts of policy makers and interventionists who aim to enhance specific health and well-being outcomes. Aging satisfaction may be an important target for future interventions aiming to improve later-life health and well-being.

          Abstract

          This cohort study uses data from the Health and Retirement Study to evaluate associations between changes in aging satisfaction and 35 subsequent health and well-being outcomes.

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          Most cited references61

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          A modified poisson regression approach to prospective studies with binary data.

          G Zou (2004)
          Relative risk is usually the parameter of interest in epidemiologic and medical studies. In this paper, the author proposes a modified Poisson regression approach (i.e., Poisson regression with a robust error variance) to estimate this effect measure directly. A simple 2-by-2 table is used to justify the validity of this approach. Results from a limited simulation study indicate that this approach is very reliable even with total sample sizes as small as 100. The method is illustrated with two data sets.
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            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.
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              Multiple Comparisons among Means

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                Author and article information

                Journal
                JAMA Netw Open
                JAMA Netw Open
                JAMA Network Open
                American Medical Association
                2574-3805
                9 February 2022
                February 2022
                9 February 2022
                : 5
                : 2
                : e2147797
                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
                [3 ]Department of Psychology, University of Michigan, Ann Arbor
                [4 ]Department of Psychology, Michigan State University, East Lansing
                [5 ]Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, Massachusetts
                [6 ]Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, Massachusetts
                [7 ]Lee Kum Sheung Center for Health and Happiness, Harvard T.H. Chan School of Public Health, Boston, Massachusetts
                Author notes
                Article Information
                Accepted for Publication: November 12, 2021.
                Published: February 9, 2022. doi:10.1001/jamanetworkopen.2021.47797
                Open Access: This is an open access article distributed under the terms of the CC-BY License. © 2022 Nakamura JS et al. JAMA Network Open.
                Corresponding Author: Julia S. Nakamura, BS, Department of Psychology, University of British Columbia, Vancouver, British Columbia, Canada, 2136 West Mall, Vancouver, BC V6T 1Z4, Canada ( jnakamura@ 123456psych.ubc.ca ).
                Author Contributions: Ms Nakamura and Dr Kim had full access to all of the data in the study and take responsibility for the integrity of the data and the accuracy of the data analysis. Drs VanderWeele and Kim are co–senior authors.
                Concept and design: Nakamura, Chen, VanderWeele, Kim.
                Acquisition, analysis, or interpretation of data: Nakamura, Hong, Smith, Chopik, VanderWeele, Kim.
                Drafting of the manuscript: Nakamura, Kim.
                Critical revision of the manuscript for important intellectual content: Nakamura, Hong, Smith, Chopik, Chen, VanderWeele, Kim.
                Obtained funding: Kim.
                Administrative, technical, or material support: Nakamura, Hong, Chopik, Kim.
                Supervision: VanderWeele, Kim.
                Conflict of Interest Disclosures: Dr VanderWeele reported receiving consulting fees from Aetna Inc. Dr Kim reported receiving consulting fees from AARP and UnitedHealth Group. No other disclosures were reported.
                Funding/Support: This work was supported by the Michael Smith Foundation for Health Research.
                Role of the Funder/Sponsor: The funding source had no role in the design and conduct of the study; collection, management, analysis, and interpretation of the data; preparation, review, or approval of the manuscript; and decision to submit the manuscript for publication.
                Additional Contributions: Sakshi Sahakari, Joanne Armstrong, and Esther Choi, BA, University of British Columbia, assisted with results table completion and manuscript formatting; they were not compensated for their contributions. Matt Wang, Tatiana Henriksson, Sofie Jensen, Katheryn Yang, Gurveer Palia, BSc, Rachel Leong, Tiana Wang, and Vanessa Kong, BA, University of British Columbia, and Caitlyn Wilson, BS, Harvard T. H. Chan School of Public Health, assisted with results table completion; they were not compensated for their contributions. This analysis uses Early Release data from the Health and Retirement Study, (Early Release Core Data 2018; Early Release Tracker File Version 1). These data have not been cleaned and may contain errors that will be corrected in the Final Public Release version of the dataset. We would like to acknowledge and thank the Health and Retirement Study, which is conducted by the Institute for Social Research at the University of Michigan, with grants from the National Institute on Aging (U01AG09740) and the Social Security Administration.
                Article
                zoi211310
                10.1001/jamanetworkopen.2021.47797
                8829664
                35138398
                cd4ded4d-c564-4340-80ef-73679eac2ea8
                Copyright 2022 Nakamura JS et al. JAMA Network Open.

                This is an open access article distributed under the terms of the CC-BY License.

                History
                : 14 September 2021
                : 12 November 2021
                Categories
                Research
                Original Investigation
                Online Only
                Public Health

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