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      Healthy lifestyle and life expectancy in people with multimorbidity in the UK Biobank: A longitudinal cohort study

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          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

          Background

          Whether a healthy lifestyle impacts longevity in the presence of multimorbidity is unclear. We investigated the associations between healthy lifestyle and life expectancy in people with and without multimorbidity.

          Methods and findings

          A total of 480,940 middle-aged adults (median age of 58 years [range 38–73], 46% male, 95% white) were analysed in the UK Biobank; this longitudinal study collected data between 2006 and 2010, and participants were followed up until 2016. We extracted 36 chronic conditions and defined multimorbidity as 2 or more conditions. Four lifestyle factors, based on national guidelines, were used: leisure-time physical activity, smoking, diet, and alcohol consumption. A combined weighted score was developed and grouped participants into 4 categories: very unhealthy, unhealthy, healthy, and very healthy. Survival models were applied to predict life expectancy, adjusting for ethnicity, working status, deprivation, body mass index, and sedentary time. A total of 93,746 (19.5%) participants had multimorbidity. During a mean follow-up of 7 (range 2–9) years, 11,006 deaths occurred. At 45 years, in men with multimorbidity an unhealthy score was associated with a gain of 1.5 (95% confidence interval [CI] −0.3 to 3.3; P = 0.102) additional life years compared to very unhealthy score, though the association was not significant, whilst a healthy score was significantly associated with a gain of 4.5 (3.3 to 5.7; P < 0.001) life years and a very healthy score with 6.3 (5.0 to 7.7; P < 0.001) years. Corresponding estimates in women were 3.5 (95% CI 0.7 to 6.3; P = 0.016), 6.4 (4.8 to 7.9; P < 0.001), and 7.6 (6.0 to 9.2; P < 0.001) years. Results were consistent in those without multimorbidity and in several sensitivity analyses. For individual lifestyle factors, no current smoking was associated with the largest survival benefit. The main limitations were that we could not explore the consistency of our results using a more restrictive definition of multimorbidity including only cardiometabolic conditions, and participants were not representative of the UK as a whole.

          Conclusions

          In this analysis of data from the UK Biobank, we found that regardless of the presence of multimorbidity, engaging in a healthier lifestyle was associated with up to 6.3 years longer life for men and 7.6 years for women; however, not all lifestyle risk factors equally correlated with life expectancy, with smoking being significantly worse than others.

          Abstract

          In a longitudinal study, Yogini Chudasama and colleagues investigate associations between life expectancy and healthy lifestyles with multimorbidity in the UK Biobank cohort.

          Author summary

          Why was this study done?
          • People with multimorbidity (presence of 2 or more chronic conditions) have poorer health outcomes and a higher mortality risk compared to people without multimorbidity.

          • A healthy lifestyle has been associated with a longer life expectancy. To our knowledge, no study to date has investigated this relationship in relation to the presence of multimorbidity.

          • Most studies used a combined score that did not account for the differential impact of each lifestyle factor on the risk of death.

          What did the researchers do and find?
          • We investigated the association between healthy lifestyle and individual risk factors with life expectancy in relation to the presence of multimorbidity.

          • We found that an overall healthy lifestyle largely counterbalances the negative association between multimorbidity and life expectancy.

          What do these findings mean?
          • A healthier lifestyle is consistently associated with a longer life expectancy across various individual risks and irrespective of the presence of multiple long-term medical conditions.

          • Public health recommendations about a healthy lifestyle to reduce the risk of developing chronic long-term conditions equally apply to individuals who have already multimorbidity.

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          Most cited references20

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          Compendium of physical activities: an update of activity codes and MET intensities.

          We provide an updated version of the Compendium of Physical Activities, a coding scheme that classifies specific physical activity (PA) by rate of energy expenditure. It was developed to enhance the comparability of results across studies using self-reports of PA. The Compendium coding scheme links a five-digit code that describes physical activities by major headings (e.g., occupation, transportation, etc.) and specific activities within each major heading with its intensity, defined as the ratio of work metabolic rate to a standard resting metabolic rate (MET). Energy expenditure in MET-minutes, MET-hours, kcal, or kcal per kilogram body weight can be estimated for specific activities by type or MET intensity. Additions to the Compendium were obtained from studies describing daily PA patterns of adults and studies measuring the energy cost of specific physical activities in field settings. The updated version includes two new major headings of volunteer and religious activities, extends the number of specific activities from 477 to 605, and provides updated MET intensity levels for selected activities.
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            The combined effects of healthy lifestyle behaviors on all cause mortality: a systematic review and meta-analysis.

            Lifestyle factors are related to mortality. Although much is known about the impact of single factors, the current evidence about the combined effects of lifestyle behaviors on mortality has not yet been systematically compiled. We searched Medline, Embase, Global Health, and Somed up to February 2012. Prospective studies were selected if they reported the combined effects of at least three of five lifestyle factors (obesity, alcohol consumption, smoking, diet, and physical activity). The mean effect sizes that certain numbers of combined lifestyle factors have on mortality were compared to the group with the least number of healthy lifestyle factors by meta-analysis. Sensitivity analyses were conducted to explore the robustness of the results. 21 studies (18 cohorts) met the inclusion criteria of which 15 were included in the meta-analysis that comprised 531,804 people with a mean follow-up of 13.24 years. The relative risks decreased proportionate to a higher number of healthy lifestyle factors for all cause mortality. A combination of at least four healthy lifestyle factors is associated with a reduction of the all cause mortality risk by 66% (95% confidence interval 58%-73%). Adherence to a healthy lifestyle is associated with a lower risk of mortality. Copyright © 2012. Published by Elsevier Inc.
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              Healthy lifestyle and life expectancy free of cancer, cardiovascular disease, and type 2 diabetes: prospective cohort study

              Abstract Objective To examine how a healthy lifestyle is related to life expectancy that is free from major chronic diseases. Design Prospective cohort study. Setting and participants The Nurses’ Health Study (1980-2014; n=73 196) and the Health Professionals Follow-Up Study (1986-2014; n=38 366). Main exposures Five low risk lifestyle factors: never smoking, body mass index 18.5-24.9, moderate to vigorous physical activity (≥30 minutes/day), moderate alcohol intake (women: 5-15 g/day; men 5-30 g/day), and a higher diet quality score (upper 40%). Main outcome Life expectancy free of diabetes, cardiovascular diseases, and cancer. Results The life expectancy free of diabetes, cardiovascular diseases, and cancer at age 50 was 23.7 years (95% confidence interval 22.6 to 24.7) for women who adopted no low risk lifestyle factors, in contrast to 34.4 years (33.1 to 35.5) for women who adopted four or five low risk factors. At age 50, the life expectancy free of any of these chronic diseases was 23.5 (22.3 to 24.7) years among men who adopted no low risk lifestyle factors and 31.1 (29.5 to 32.5) years in men who adopted four or five low risk lifestyle factors. For current male smokers who smoked heavily (≥15 cigarettes/day) or obese men and women (body mass index ≥30), their disease-free life expectancies accounted for the lowest proportion (≤75%) of total life expectancy at age 50. Conclusion Adherence to a healthy lifestyle at mid-life is associated with a longer life expectancy free of major chronic diseases.
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                Author and article information

                Contributors
                Role: Formal analysisRole: InvestigationRole: MethodologyRole: Project administrationRole: Writing – original draftRole: Writing – review & editing
                Role: ConceptualizationRole: MethodologyRole: SupervisionRole: Writing – review & editing
                Role: MethodologyRole: SupervisionRole: Writing – review & editing
                Role: ConceptualizationRole: Data curationRole: Writing – review & editing
                Role: Writing – review & editing
                Role: Writing – review & editing
                Role: MethodologyRole: SupervisionRole: Writing – review & editing
                Role: Academic Editor
                Journal
                PLoS Med
                PLoS Med
                plos
                plosmed
                PLoS Medicine
                Public Library of Science (San Francisco, CA USA )
                1549-1277
                1549-1676
                22 September 2020
                September 2020
                : 17
                : 9
                : e1003332
                Affiliations
                [1 ] Diabetes Research Centre, Leicester General Hospital, University of Leicester, Leicester, United Kingdom
                [2 ] National Institute for Health Research (NIHR) Applied Research Collaboration—East Midlands (ARC-EM) Leicester Diabetes Centre, Leicester, United Kingdom
                [3 ] National Institute for Health Research (NIHR) Leicester Biomedical Research Centre, Leicester Diabetes Centre, Leicester, United Kingdom
                Harvard Medical School, UNITED STATES
                Author notes

                I have read the journal's policy and the authors of this manuscript have the following competing interests. FZ is funded with an unrestricted educational grant from the NIHR CLAHRC East Midlands to the University of Leicester. KK has acted as a consultant and speaker for Novartis, Novo Nordisk, Sanofi-Aventis, Lilly, Servier, and Merck Sharp & Dohme. He has received grants in support of investigator and investigator-initiated trials from Novartis, Novo Nordisk, Sanofi-Aventis, Lilly, Pfizer, Boehringer Ingelheim, and Merck Sharp & Dohme. KK has received funds for research and honoraria for speaking at meetings and has served on advisory boards for Lilly, Sanofi-Aventis, Merck Sharp & Dohme, and Novo Nordisk. MJD has acted as consultant, advisory board member, and speaker for Novo Nordisk, Sanofi-Aventis, Lilly, Merck Sharp & Dohme, Boehringer Ingelheim, AstraZeneca, and Janssen; an advisory board member for Servier and Gilead Sciences Ltd; and as a speaker for NAPP, Mitsubishi Tanabe Pharma Corporation, and Takeda Pharmaceuticals International Inc. TY has received funding from the Leicester NIHR Leicester BRC. All other authors have declared that no competing interests exist.

                Author information
                http://orcid.org/0000-0002-6777-0064
                http://orcid.org/0000-0003-2343-7099
                http://orcid.org/0000-0002-9987-9371
                http://orcid.org/0000-0002-2636-6487
                Article
                PMEDICINE-D-20-01260
                10.1371/journal.pmed.1003332
                7508366
                32960883
                cb750b5d-bf8c-4207-abd0-fe67bcbb2b63
                © 2020 Chudasama 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
                : 6 April 2020
                : 18 August 2020
                Page count
                Figures: 2, Tables: 3, Pages: 18
                Funding
                Funded by: University of Leicester
                Award Recipient :
                YC is funded by a University of Leicester College of Medicine, Biological Sciences and Psychology PhD studentship in collaboration with Collaboration for Leadership in Applied Health Research and Care East Midlands (CLAHRC EM), now recommissioned as NIHR Applied Research Collaboration East Midlands (ARC EM). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
                Categories
                Research Article
                Biology and Life Sciences
                Population Biology
                Population Metrics
                Life Expectancy
                Medicine and Health Sciences
                Public and Occupational Health
                Life Expectancy
                Biology and Life Sciences
                Nutrition
                Diet
                Alcohol Consumption
                Medicine and Health Sciences
                Nutrition
                Diet
                Alcohol Consumption
                Medicine and Health Sciences
                Epidemiology
                Medical Risk Factors
                Medicine and Health Sciences
                Public and Occupational Health
                Physical Activity
                Biology and Life Sciences
                Nutrition
                Diet
                Medicine and Health Sciences
                Nutrition
                Diet
                Biology and Life Sciences
                Psychology
                Behavior
                Sedentary Behavior
                Social Sciences
                Psychology
                Behavior
                Sedentary Behavior
                Biology and Life Sciences
                Physiology
                Physiological Parameters
                Body Weight
                Body Mass Index
                Medicine and Health Sciences
                Public and Occupational Health
                Custom metadata
                The data that support the findings of this study are available from the UK Biobank project site, subject to registration and application process. Further details can be found at https://www.ukbiobank.ac.uk.

                Medicine
                Medicine

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