The Validity and Value of Self-reported Physical Activity and Accelerometry in People With Schizophrenia: A Population-Scale Study of the UK Biobank

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Abstract

Background

Previous physical activity (PA) research in schizophrenia has relied largely upon self-report measures. However, the accuracy of this method is questionable. Obtaining accurate measurements, and determining what may influence PA levels in schizophrenia, is essential to understand physical inactivity in this population. This study examined differences in self-reported and objectively measured PA in people with schizophrenia and the general population using a large, population-based dataset from the UK Biobank.

Methods

Baseline data from the UK Biobank (2007–2010) were analyzed; including 1078 people with schizophrenia (54.19 ± 8.39 years; 55% male) and 450549 without (56.44 ± 8.11; 46% male). We compared self-reported PA with objectively measured accelerometry data in schizophrenia and comparison samples. We also examined correlations between self-report and objective measures.

Results

People with schizophrenia reported the same PA levels as those without, with no differences in low, moderate, or vigorous intensity activity. However, accelerometry data showed a large and statistically significant reduction of PA in schizophrenia; as people with schizophrenia, on average, engaged in less PA than 80% of the general population. Nonetheless, within the schizophrenia sample, total self-reported PA still held significant correlations with objective measures.

Conclusions

People with schizophrenia are significantly less active than the general population. However, self-report measures in epidemiological studies fail to capture the reduced activity levels in schizophrenia. This also has implications for self-report measures of other lifestyle factors which may contribute toward the poor health outcomes observed in schizophrenia. Nonetheless, self-report measures may still be useful for identifying how active individuals with schizophrenia relative to other patients.

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Most cited references 19

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New Tools for New Research in Psychiatry: A Scalable and Customizable Platform to Empower Data Driven Smartphone Research

John Torous, Mathew V. Kiang, Jeanette Lorme … (2016)

Background A longstanding barrier to progress in psychiatry, both in clinical settings and research trials, has been the persistent difficulty of accurately and reliably quantifying disease phenotypes. Mobile phone technology combined with data science has the potential to offer medicine a wealth of additional information on disease phenotypes, but the large majority of existing smartphone apps are not intended for use as biomedical research platforms and, as such, do not generate research-quality data. Objective Our aim is not the creation of yet another app per se but rather the establishment of a platform to collect research-quality smartphone raw sensor and usage pattern data. Our ultimate goal is to develop statistical, mathematical, and computational methodology to enable us and others to extract biomedical and clinical insights from smartphone data. Methods We report on the development and early testing of Beiwe, a research platform featuring a study portal, smartphone app, database, and data modeling and analysis tools designed and developed specifically for transparent, customizable, and reproducible biomedical research use, in particular for the study of psychiatric and neurological disorders. We also outline a proposed study using the platform for patients with schizophrenia. Results We demonstrate the passive data capabilities of the Beiwe platform and early results of its analytical capabilities. Conclusions Smartphone sensors and phone usage patterns, when coupled with appropriate statistical learning tools, are able to capture various social and behavioral manifestations of illnesses, in naturalistic settings, as lived and experienced by patients. The ubiquity of smartphones makes this type of moment-by-moment quantification of disease phenotypes highly scalable and, when integrated within a transparent research platform, presents tremendous opportunities for research, discovery, and patient health.

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Mortality gap for people with bipolar disorder and schizophrenia: UK-based cohort study 2000–2014†

Joseph Hayes, Louise Marston, Kate Walters … (2017)

Background Bipolar disorder and schizophrenia are associated with increased mortality relative to the general population. There is an international emphasis on decreasing this excess mortality. Aims To determine whether the mortality gap between individuals with bipolar disorder and schizophrenia and the general population has decreased. Method A nationally representative cohort study using primary care electronic health records from 2000 to 2014, comparing all patients diagnosed with bipolar disorder or schizophrenia and the general population. The primary outcome was all-cause mortality. Results Individuals with bipolar disorder and schizophrenia had elevated mortality (adjusted hazard ratio (HR) = 1.79, 95% CI 1.67–1.88 and 2.08, 95% CI 1.98–2.19 respectively). Adjusted HRs for bipolar disorder increased by 0.14/year (95% CI 0.10–0.19) from 2006 to 2014. The adjusted HRs for schizophrenia increased gradually from 2004 to 2010 (0.11/year, 95% CI 0.04–0.17) and rapidly after 2010 (0.34/year, 95% CI 0.18–0.49). Conclusions The mortality gap between individuals with bipolar disorder and schizophrenia, and the general population is widening.

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Associations of objectively measured sedentary behaviour and physical activity with markers of cardiometabolic health.

K Khunti, M A Nimmo, S Biddle … (2013)

The study aimed to examine the associations between objectively measured sedentary time, breaks in sedentary time, moderate-to-vigorous physical activity (MVPA) and total physical activity with markers of cardiometabolic health in a population with known risk factors for type 2 diabetes mellitus. This study reports data from two ongoing diabetes prevention programmes. Participants with known risk factors were recruited from primary care practices located within the East Midlands, UK, over the period 2010-2011. ActiGraph GT3X accelerometers (15 s epochs) were used to assess sedentary time (<25 counts per 15 s), MVPA (≥ 488 counts per 15 s) and total physical activity (total counts). A break was considered as any interruption in sedentary time (≥ 25 counts per 15 s). Linear regression examined the independent association of sedentary time, breaks in sedentary time, MVPA and total physical activity with markers of cardiometabolic health. The sample comprised 878 participants; 153 from Project STAND (Sedentary Time And Diabetes) (age 32.9 ± 5.6 years, 28.8% male) and 725 from Walking Away from Diabetes (age 63.7 ± 7.8 years, 64.8% male). Following adjustment for various covariates, including MVPA and BMI, there were detrimental linear associations of sedentary time with 2 h plasma glucose (standardised beta coefficient) (β = 0.220, p < 0.001), triacylglycerol (β = 0.206, p = 0.001) and HDL-cholesterol (β = -0.123, p = 0.029). Breaks in sedentary time, total physical activity and MVPA were significantly inversely associated with measures of adiposity, but not with any other cardiometabolic variables after adjustment for sedentary time and BMI. In adults at high risk of type 2 diabetes mellitus, time spent sedentary is strongly and adversely associated with cardiometabolic health and may be a more important indicator of poor health than MVPA.

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Author and article information

Journal

Journal ID (nlm-ta): Schizophr Bull

Journal ID (iso-abbrev): Schizophr Bull

Journal ID (publisher-id): schbul

Title: Schizophrenia Bulletin

Publisher: Oxford University Press (US )

ISSN (Print): 0586-7614

ISSN (Electronic): 1745-1701

Publication date (Print): October 2018

Publication date (Electronic): 24 October 2017

Publication date PMC-release: 24 October 2017

Volume: 44

Issue: 6

Pages: 1293-1300

Affiliations

[1 ]NICM, School of Science and Health, University of Western Sydney, Sydney, Australia

[2 ]Division of Psychology and Mental Health, Faculty of Biology, Medicine and Health, University of Manchester, Manchester, UK

[3 ]Physiotherapy Department, South London and Maudsley NHS Foundation Trust, London, UK

[4 ]Health Service and Population Research Department, Institute of Psychiatry, Psychology and Neuroscience, King’s College London, London, UK

[5 ]Department of Rehabilitation Sciences, KU Leuven, Leuven, Belgium

[6 ]Department of Neurosciences, UPC KU Leuven, Leuven, Belgium

[7 ]Hospital de Clínicas de Porto Alegre, Porto Alegre, Brazil

[8 ]Centro Universitário La Salle, Canoas, Brazil

[9 ]Black Dog Institute, Randwick, Australia

[10 ]School of Psychiatry, University of New South Wales, Sydney, Australia

[11 ]Schizophrenia Research Unit, Ingham Institute of Applied Medical Research, Liverpool, Australia

[12 ]Department of Zoology, Edward Grey Institute, University of Oxford, Oxford, UK

[13 ]Department of Psychiatry, University of Melbourne, The Melbourne Clinic, Melbourne, Australia

[14 ]Greater Manchester Mental Health Foundation Trust, Manchester, UK

Author notes

To whom correspondence should be addressed; NICM, School of Science and Health, University of Western Sydney, Campbelltown, Sydney, NSW 2560, Australia; tel: +61-(0)-451-231-815, Fax: +447-724-458-525; e-mail: j.firth@ 123456westernsydney.edu

Article

Publisher ID: sbx149

DOI: 10.1093/schbul/sbx149

PMC ID: 6192495

PubMed ID: 29069474

SO-VID: 3deab75c-bb35-4e3b-8039-82b36d706d47

License:

This is an Open Access article distributed under the terms of the Creative Commons Attribution License ( http://creativecommons.org/licenses/by/4.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited.

History

Page count

Pages: 8

Funding

Funded by: National Institute for Health Research 10.13039/501100000272

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The Validity and Value of Self-reported Physical Activity and Accelerometry in People With Schizophrenia: A Population-Scale Study of the UK Biobank

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Karger: Cardiovascular System

Most cited references 19

New Tools for New Research in Psychiatry: A Scalable and Customizable Platform to Empower Data Driven Smartphone Research

Mortality gap for people with bipolar disorder and schizophrenia: UK-based cohort study 2000–2014†

Associations of objectively measured sedentary behaviour and physical activity with markers of cardiometabolic health.

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