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      Cross-sectional associations of neighbourhood socioeconomic disadvantage and greenness with accelerometer-measured leisure-time physical activity in a cohort of ageing workers

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          Abstract

          Objective

          Neighbourhood characteristics may affect the level of physical activity (PA) of the residents. Few studies have examined the combined effects of distinctive neighbourhood characteristics on PA using objective data or differentiated between activity during working or non-working days. We examined the associations of socioeconomic disadvantage and greenness with accelerometer-measured leisure-time PA during working and non-working days.

          Design

          Cross-sectional study.

          Setting

          Finnish Retirement and Aging (FIREA) study.

          Participants

          708 workers (604 women, mean age 62.4 ranging from 58 to 64 years,) participating in the FIREA study who provided PA measurement data for at least 1 working and non-working day.

          Primary and secondary outcomes

          PA was measured with wrist-worn accelerometer on average of 4 working and 2 non-working days. Outcomes were total PA, light PA (LPA) and moderate-to-vigorous PA (MVPA). These measurements were linked to data on neighbourhood socioeconomic disadvantage and greenness within the home neighbourhood (750×750 m). Generalised linear models were adjusted for possible confounders.

          Results

          On non-working days, higher neighbourhood disadvantage associated with lower levels of total PA (p value=0.07) and higher level of neighbourhood greenness associated with higher level of total PA (p value=0.04). Neighbourhood disadvantage and greenness had an interaction (p value=0.02); in areas of low disadvantage higher greenness did not associate with the level of total PA. However, in areas of high disadvantage, 2 SD higher greenness associated with 46 min/day (95% CI 8.4 to 85) higher total PA. Slightly stronger interaction was observed for LPA (p=0.03) than for the MVPA (p=0.09). During working days, there were no associations between neighbourhood characteristics and leisure-time total PA.

          Conclusions

          Of the disadvantaged neighbourhoods, those characterised by high levels of greenness seem to associate with higher levels of leisure-time PA during non-working days. These findings suggest that efforts to add greenness to socioeconomically disadvantaged neighbourhoods might reduce inequalities in PA.

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          Most cited references47

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          Google Earth Engine: Planetary-scale geospatial analysis for everyone

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            A comparison of direct versus self-report measures for assessing physical activity in adults: a systematic review

            Background Accurate assessment is required to assess current and changing physical activity levels, and to evaluate the effectiveness of interventions designed to increase activity levels. This study systematically reviewed the literature to determine the extent of agreement between subjectively (self-report e.g. questionnaire, diary) and objectively (directly measured; e.g. accelerometry, doubly labeled water) assessed physical activity in adults. Methods Eight electronic databases were searched to identify observational and experimental studies of adult populations. Searching identified 4,463 potential articles. Initial screening found that 293 examined the relationship between self-reported and directly measured physical activity and met the eligibility criteria. Data abstraction was completed for 187 articles, which described comparable data and/or comparisons, while 76 articles lacked comparable data or comparisons, and a further 30 did not meet the review's eligibility requirements. A risk of bias assessment was conducted for all articles from which data was abstracted. Results Correlations between self-report and direct measures were generally low-to-moderate and ranged from -0.71 to 0.96. No clear pattern emerged for the mean differences between self-report and direct measures of physical activity. Trends differed by measure of physical activity employed, level of physical activity measured, and the gender of participants. Results of the risk of bias assessment indicated that 38% of the studies had lower quality scores. Conclusion The findings suggest that the measurement method may have a significant impact on the observed levels of physical activity. Self-report measures of physical activity were both higher and lower than directly measured levels of physical activity, which poses a problem for both reliance on self-report measures and for attempts to correct for self-report – direct measure differences. This review reveals the need for valid, accurate and reliable measures of physical activity in evaluating current and changing physical activity levels, physical activity interventions, and the relationships between physical activity and health outcomes.
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              GGIR: A Research Community–Driven Open Source R Package for Generating Physical Activity and Sleep Outcomes From Multi-Day Raw Accelerometer Data

              Recent technological advances have transformed the research on physical activity initially based on questionnaire data to the most recent objective data from accelerometers. The shift to availability of raw accelerations has increased measurement accuracy, transparency, and the potential for data harmonization. However, it has also shifted the need for considerable processing expertise to the researcher. Many users do not have this expertise. The R package GGIR has been made available to all as a tool to convermulti-day high resolution raw accelerometer data from wearable movement sensors into meaningful evidence-based outcomes and insightful reports for the study of human daily physical activity and sleep. This paper aims to provide a one-stop overview of GGIR package, the papers underpinning the theory of GGIR, and how research contributes to the continued growth of the GGIR package. The package includes a range of literature-supported methods to clean the data and provide day-by-day, as well as full recording, weekly, weekend, and weekday estimates of physical activity and sleep parameters. In addition, the package also comes with a shell function that enables the user to process a set of input files and produce csv summary reports with a single function call, ideal for users less proficient in R. GGIR has been used in over 90 peer-reviewed scientific publications to date. The evolution of GGIR over time and widespread use across a range of research areas highlights the importance of open source software development for the research community and advancing methods in physical behavior research.
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                Author and article information

                Journal
                BMJ Open
                BMJ Open
                bmjopen
                bmjopen
                BMJ Open
                BMJ Publishing Group (BMA House, Tavistock Square, London, WC1H 9JR )
                2044-6055
                2020
                16 August 2020
                : 10
                : 8
                : e038673
                Affiliations
                [1 ]departmentHealth Security , Finnish Institute for Health and Welfare , Helsinki, Finland
                [2 ]departmentFaculty of Medicine , University of Helsinki , Helsinki, Finland
                [3 ]departmentCentre for Population Health Research , University of Turku , Turku, Finland
                [4 ]departmentDepartment of Public Health , University of Turku , Turku, Finland
                [5 ]departmentPublic Health Solutions , Finnish Institute for Health and Welfare , Helsinki, Finland
                [6 ]departmentGeoinformatics Services , Finnish Environment Institute , Helsinki, Finland
                [7 ]departmentDepartment of Geography and Geology , University of Turku , Turku, Finland
                [8 ]departmentDepartment of Epidemiology and Public Health , University College London , London, UK
                [9 ]departmentDepartment of Society Human Development , Harvard University T H Chan School of Public Health , Boston, Massachusetts, USA
                Author notes
                [Correspondence to ] Dr Sari Stenholm; sari.stenholm@ 123456utu.fi
                Author information
                http://orcid.org/0000-0003-1142-0388
                http://orcid.org/0000-0002-6036-061X
                http://orcid.org/0000-0001-7560-0930
                Article
                bmjopen-2020-038673
                10.1136/bmjopen-2020-038673
                7430423
                32801206
                c8bbcf74-a410-42cc-b664-1fc7aa2b2d84
                © Author(s) (or their employer(s)) 2020. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ.

                This is an open access article distributed in accordance with the Creative Commons Attribution Non Commercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited, appropriate credit is given, any changes made indicated, and the use is non-commercial. See:  http://creativecommons.org/licenses/by-nc/4.0/.

                History
                : 19 March 2020
                : 17 June 2020
                : 03 July 2020
                Funding
                Funded by: FundRef http://dx.doi.org/10.13039/501100003126, Opetus- ja Kulttuuriministeriö;
                Award ID: to SS
                Funded by: FundRef http://dx.doi.org/10.13039/501100002341, Academy of Finland;
                Award ID: 286294
                Award ID: 294154
                Award ID: 319246
                Award ID: 331492
                Funded by: FundRef http://dx.doi.org/10.13039/501100004212, Päivikki ja Sakari Sohlbergin Säätiö;
                Award ID: to AP
                Funded by: Helsinki Institute of Life Sciences;
                Award ID: to MK
                Categories
                Public Health
                1506
                1724
                Original research
                Custom metadata
                unlocked

                Medicine
                preventive medicine,public health,sports medicine,social medicine
                Medicine
                preventive medicine, public health, sports medicine, social medicine

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