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. 2019 Mar;39(3):67–103. doi: 10.24095/hpcdp.39.3.01

Evidence synthesis Where are children and adults physically active and sedentary? – a rapid review of location-based studies

Stephanie A Prince 1,2, Gregory P Butler 1, Deepa P Rao 1, Wendy Thompson 1
PMCID: PMC6478053  PMID: 30869472

Abstract

Introduction:

Geographical positioning systems (GPS) have the capacity to provide further context around where physical activity (PA) and sedentary time (ST) are accrued especially when overlaid onto objectively measured movement. The objective of this rapid review was to summarize evidence from location-based studies which employed the simultaneous use of GPS and objective measures of PA and/or ST.

Methods:

Six databases were searched to identify studies that employed the simultaneous use of GPS and objective measures of PA or ST to quantify location of movement. Risk of bias was assessed, and a qualitative synthesis completed.

Results:

Searching identified 3446 articles; 59 were included in the review. A total of 22 studies in children, 17 in youth and 20 in adults were captured. The active transportation environment emerged as an important location for moderate-to-vigorous intensity physical activity (MVPA) in children, youth and adults. In children and youth, the school is an important location for MVPA, especially the schoolyard for children. Indoor locations (e.g., schools, homes) appear to be greater sources of lighter intensities of PA and ST. The review was limited by a lack of standardization in the nomenclature used to describe the locations and methods, as well as measures of variance.

Conclusion:

Evidence suggests that the active transportation environment is a potentially important contributor of MVPA across an individual’s lifespan. There is a need for future location-based studies to report on locations of all intensity of movement (including minutes and proportion) using a whole-day approach in larger representative samples.

Keywords: motor activity; sedentary time; location, built environment; active transportation

Highlights

  • The active transportation environment is an important location for physical activity in children, youth and adults.

  • Among children and youth, the school (especially the schoolyard) is an important location for physical activity.

  • Indoor locations (e.g., schools, homes) appear to be greater sources of lighter intensities of physical activity and sedentary time.

Introduction

Greater physical activity (PA) and lower sedentary time (ST) have been shown to independently play a role in the prevention of chronic conditions (e.g., cardiovascular disease, diabetes, obesity and cancer).1,2 While the importance of these health behaviours is largely acknowledged, the majority of children and adults do not meet current PA guidelines and spend most of their days engaged in sedentary behaviour.3-5 Further, PA levels decline with age, and sex differences in PA are often observed.6,7 The built environment refers to our physical surroundings and includes for example parks, workplaces, schools, active transportation infrastructure, and homes among many others. The built environment has been associated with levels of PA and ST.8,9

Much of the evidence around the relationship between the built environment and PA/ST has come from cross-sectional studies which obtain contextual information (e.g., presence of parks in the neighbourhood) from either self-report perceptions of environment or by using geographical information systems (GIS) and associations with movement (largely based on self-report).10-12 While this information can provide an assessment of environmental exposure, it cannot always infer direct causality for where an individual’s behaviour actually occurs. Context-specific patterns of movement refer to movement that occurs within specific domains or locations. Context-specific studies have examined behaviours which occur in locations such as neighbourhoods13 or parks14 through direct observation or mapping and can provide detailed information about what parts of the environment individuals interact with (e.g., paths within a park, play structures, etc.). However, these studies are often limited to one location/domain and can be time and resource intensive to conduct.

The advent of newer technologies to track an individual’s location such as geographic positioning systems (GPS) have the capacity to provide further context around where PA and ST are accrued.15-17 Additionally, the overlay of GPS onto objectively measured movement data allows for a more robust quantification of behaviour within locations and has the capacity to provide a more comprehensive picture of an individual’s activity space.18 Providing greater context can facilitate a better understanding of the locations in which behaviours are undertaken and whether they differ across the life span and between sexes. The objective of this review was to identify and summarize evidence from location-based studies which employed the simultaneous use of GPS and objectively measured PA or ST.

Methods

A rapid review was employed; the protocol was prospectively registered with PROSPERO (see: https://www.crd.york.ac .uk/prospero/; #CRD42018084640). A rapid review employs general systematic review methodology but allows modifications for a quicker time to publication. This rapid review employed systematic review methodology but relied upon a single screener and data abstractor with support from data verification checks.

Criteria for considering studies for this review

Population

Data from high-income Organization for Economic Co-operation and Development (OECD) countries19 and apparently healthy populations were included. Findings were grouped into children (3–11 years), youth (12–17 years) and adults (≥ 18 years).

Exposures

The review included studies that used GPS information to objectively identify location of movement behaviour. GPS technologies included the Global Navigation Satellite System to determine location, direction and speed of the device.20 For the purpose of the review, active transportation was included as a location term to define the location of behaviours that were specific to transportation, that weren’t reflected by other locations (e.g., journey from home to school).

Outcomes

Studies must have used an objective measure of movement including pedometers, heart rate monitors and accelerometers to define time spent sedentary, time spent in light intensity physical activity (LPA), in moderate intensity physical activity (MPA) and in vigorous intensity physical activity (VPA).

Study design

Observational (prospective cohort, crosssectional and case-control) and experimental (randomized controlled trials, pre-post and quasi-experimental) studies were included. Reviews and qualitative studies were excluded.

Publication status and language

Only publications in English or French, and published studies and indexed dissertations were eligible.

Search strategy

A comprehensive search strategy was developed in collaboration with two research librarians. The following six bibliographic databases were searched: Ovid MEDLINE(R) In-Process (1946 to January 5, 2018); Ovid EMBASE (1974 to January 5, 2018); Ovid PsycINFO (1806 to January Week 1, 2018); EBSCO CINAHL (1982 to January 5, 2018); EBSCO SportDISCUS (1830 to November Week 2, 2017); and, ProQuest Dissertations & Theses Global (1743 to January 5, 2018). The search strategy used for MEDLINE is included in Table 1. Bibliographies of key review papers were also searched.

Table 1. Ovid MEDLINE search strategy.

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Selection of studies

Articles were imported into RefWorks (RefWorks, Bethesda, MD, USA) and, after removal of duplicates, exported to Microsoft Excel for screening. A single reviewer (SAP) screened the titles, abstracts and full texts of all studies. In the event that the reviewer was unsure, a co-author (GPB) was consulted.

Data extraction and analysis

Data abstraction forms were completed in Microsoft Excel by one reviewer (SAP) and a random 10% sample verified by another (AM). Information extracted included: publication details (author, year, location); sample size; study design; participant characteristics (age, sex, population); data collection period (e.g., seven days of wear); GPS monitor; movement monitor and cutpoints (e.g., ST < 100 counts/minute); locations assessed (e.g., home, work, school, transportation, park); outcome assessed (e.g., ST, LPA, moderate-to-vigorous intensity physical activity [MVPA], steps); and, description of outcome.

Due to heterogeneity in reporting outcomes across studies and lack of reporting on variance, the review uses a qualitative synthesis. Insufficient data was available to examine differences by level of socioeconomic status, location cost or by country. Sex differences are discussed where available.

Risk of bias appraisal

The risk of bias of individual studies was assessed using a modified version of the Cochrane Collaboration's Tool for Assessing Risk of Bias.21 Studies were assessed for potential biases including: selection bias (sampling methods); performance and detection bias (measurement issues); attrition bias (incomplete follow-up and > 10% missing data), selective reporting bias (selective/incomplete reporting, rated high if secondary data analyses); and other possible sources of bias (i.e., inadequate adjustment for sex and wear time).

Results

Description of studies

Figure 1 provides details of the literature search and screening process. Of the 3446 originally identified citations, 945 were identified in MEDLINE, 953 in EMBASE, 619 in PsycINFO, 207 in CINAHL, 260 in SPORTDiscus, 459 in Dissertations and Theses, and 3 from other sources. A total of 59 studies met the eligibility criteria. Study characteristics and findings are presented in Table 2. The review includes studies published over a 13-year period (2005 to 2017) and conducted in 12 countries with the majority from the United States (US) and the United Kingdom (UK); three were Canadian. The most widely used GPS and activity monitor devices were the QStarz Q-1000XT and ActiGraph, respectively. The most common locations included: home, school, workplace, active transportation, parks/playgrounds, and green spaces. Many locations were defined using buffers around the centre of an address (e.g., 50 m around home). MVPA was the most studied behaviour. There are a total of 22 studies in children,22-43 17 in youth44-60 and 20 in adults.28,61-79 Sample sizes ranged from 12 to 1053; 39% were small (N ≤ 100).

Figure 1. Flow diagram of the literature search and screening process.

Figure 1

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Table 2. Included study characteristics and summary of findings.

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Risk of bias assessment

Risk of bias results are summarized in Figure 2. Just over half of the studies had a high risk of selection bias as many included convenience samples. About a quarter had no description of how the study sample was derived. The majority had a low risk of performance and detection bias since they mostly employed GPS technology overlaid using GIS and used accelerometers with valid cut-points to define ST, LPA and MVPA. However, some studies had a high risk of performance bias as there was potential for misclassification of location based on the decisions of coders and/or the use of ‘buffers’ to define spaces. Slightly less than half of the studies had a high risk of selective reporting; many conducted secondary analyses for which the primary objective of the study was not to examine location of movement. Finally, most studies had a high risk of ‘other’ bias which included the lack of adjustment for wear time and sex in analyses.

Figure 2. Risk of bias summary.

Figure 2

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Location-based findings for children (3-11 years)

The most commonly reported locations in the child studies were: homes, schools, parks, active transportation, and streets/ roads. Results suggest that the active transportation and school environments are important locations for MVPA, while the home environment is less of a contributor.

Many studies focussed on movement patterns within specific sub-sets of environments rather than total-day movement. For example, several studies examined or reported exclusively on time spent in travel to-and-from school.26,32,34,41 In these studies, a substantial proportion of time (31-37%) spent commuting to school was spent in MVPA26,34 and contributed to 11-22% of total MVPA (especially among walkers).32,41 Children who walked to school tended to live closer than those who use passive modes of transit.26

Additional studies identified streets/roads as great sources of MVPA among children,35 largely owing to their use for active transit to-and-from school.39

Consistent evidence suggests that the school environment is one of the greatest sources for total MVPA23,27,30,35,39,42 for children. Specifically, the schoolyard appears to be a large contributor to school-based MVPA, especially among boys.27,42 The Spatial Planning and Children’s Exercise (SPACE) Study in the Netherlands found that children spent a very small proportion of the time (2-3%) inside the school building in MVPA; the schoolyard (especially at recess) was a greater contributor.27 Similarly, children from the Active Living Study obtained 18% of their daily MVPA in the schoolyard.42

While parks and green space were low contributors of total MVPA,40 time spent within these spaces was often at higher intensities.23,24,29,43 The Children’s Activity in their Local Environment (CALE) Study from New Zealand found that only 2% of recorded PA took place in city parks.40 Data from the Healthy PLACES study in the US found that only 27% of children used a neighbourhood park and proximity was directly related to use.29

Indoor locations appear to be a substantial source of LPA25 and ST,22 while outdoor locations contribute more to MVPA.24,30,43There is likely a seasonal effect on location of MVPA. Oreskovic et al.37 found that MVPA was higher in the home environment during winter months and higher in parks/playgrounds during the summer months.

Much of time in the home environment is spent sedentary and appears to be a substantial source of ST.22-24,28 Dunton et al.28found that 76% of parent-child ST was spent in the home. A study of preschoolers found that 45% of time spent in the home environment was spent sedentary.24Burgi et al.23 found that 7- to 9-year-olds spent a median of 60% of their home time sedentary. Results from the Healthy PLACES study also found that among 8- to 14-yearolds, ST often occurred in the home.22

Several studies reported on sex differences in locations for MVPA. One study found that boys obtained a higher proportion of their MVPA outside their neighbourhood (> 800 m), while girls obtained a higher proportion inside their neighbourhood.31 Two studies observed that active transportation is an important location of MVPA, especially among girls. The home-school journey was found to contribute a greater proportion of daily MVPA among girls compared to boys (36% vs. 31%) in one study41 while another found that girls engaged in more active transportation compared to boys (29% vs. 26%), which in turn contributed to a greater percent of total MVPA (55% vs. 35%).39 Boys were found to obtain a greater proportion of their daily MVPA at school39 and in schoolyards compared to girls.42 Other studies found no sex differences in location of ST, light intensity PA or MVPA.25,30,32,38,41

Location-based findings for youth (12-17 years)

The most commonly reported locations in youth were: homes; schools; recreational facilities; active transportation; and, green space. Many focussed exclusively on MVPA within the active transportation environment, specifically the commute toand- from school.47,55,59,60 Collins et al.47 in their study of youth from England found that active commuting contributed to 35% of daily MVPA. Commuting distance appears to be a significant predictor of active transportation, with active commuters often living closer to the destination than passive commuters.47,55,60

Roads and sidewalks are major sources of youth MVPA,45,51,53 largely owing to their use for active transit.49,56 A Canadian study found that urban youth accumulated the majority (56% for girls, 58% for boys) of their daily MVPA while commuting (largely to-and-from school); this was greater than for suburban and rural students.56

Similar to children, the school environment is one of the greatest sources of MVPA among youth;45,46,49,50,53,54,56 likely reflective of the location where they spend a substantial amount of their day. However, Carlson et al.46 using data from the US-based TEAN Study, found that although most (55% on school days) MVPA was achieved at school, relative to the proportion of time spent at school, it was a low amount.

Contrary to findings for children, the home environment was found to be a large contributor of MVPA in several studies, 45,46,52 especially on non-school days46and in suburban and rural compared to urban youth.56 A couple of studies, however, noted that the home environment was less of a contributor.49,53

Evidence around green space as a contributor of total MVPA is mixed. Results of the GAG Study in Scotland found that green space accounted for only 11% of leisure time MVPA.48 Whereas, the When Cities Move Children (WCMC) Study in Denmark found urban green space was a major contributor of daily outdoor MVPA.50Lachowycz et al.51 reported that green space and parks were responsible for 46% and 29% of all weekend outdoor MVPA, respectively.

Very few youth studies reported on locations for LPA and ST.51-53 Similar to findings for children in this regard, indoor locations appear to be greater sources of LPA51 and ST.51,53

Few studies reported on sex analyses. Boys were found to achieve more MVPA outside compared to girls.45 Studies have found that boys obtain more MVPA compared to girls at school,45,46,49 in transport49 and at home,46 but that girls had more MVPA near school.46 Rainham et al.56 found sex differences in suburban and rural, but not urban youth. Suburban boys obtained more of their MVPA at home than suburban girls (30% vs. 20%). While suburban girls spent more of their MVPA time commuting compared to suburban boys (42.5% vs. 27.4%), rural girls spent less of their MVPA time commuting compared to rural boys (20.7% vs. 27.0%).56 Collins et al.47 found no sex differences in active commuting.

Location-based findings for adults (≥ 18 years)

The most commonly reported locations in adult studies were: home neighbourhood; home; outside home neighbourhood; parks; green space; active transportation; and, commercial destinations. Evidence suggests that among adults the active transportation environment is one of the greatest sources while the home environment is one of the least common locations of MVPA.

Several studies examined or reported exclusively on time spent in active transportation. 61-64,74 Commuting/active transportation accounted for between 33% and 68% of total daily MVPA.61,63,74 Chaix et al.63 found that in general transportation accounted for a median of 13% of ST, but public transportation trips were associated with significantly more ST compared to personalized motor vehicle trips. Costa et al.64 found that the mode of transportation during a journey was related to the median proportion of time spent in ST, LPA and MVPA. Journey time spent in ST was highest in car- (59%) and bus-only (~41%) journeys, time spent in LPA was greatest among trips that used a combination of car (38%) or car and cycling or walking (~33-35%) or bus-only trips (~29%), and journey time spent in MVPA was greatest in walking- (100%) or cycling-only (~33% MPA + 56% VPA) trips. Approximately 20% of bus-only trip time was spent in MVPA.64

Several studies examined time spent in the home environment.65,68,69,74,75,78 The home environment appears to be associated with ST and LPA,28,65,69 but not MVPA with most MVPA occurring outside of the home area,69,74,75 especially on weekdays.75 In contrast, the US-based System for Observing Play and Recreation in Communities (SOPARC) Study found that homes accounted for 20-29% of boutbased MVPA, whereas roads and fitness facilities were important locations for VPA.68

The evidence around parks and green space was mixed, but generally identified that both locations are potential sources of MVPA65 (though not necessarily substantial amounts66,71) among adults, depending on whether they are actually used.66,77 Data from the SOPARC study found that only 12% of time in parks was spent engaged in MVPA66 and that this represented ~13% of total daily MVPA.68

While few studies commented on the workplace environment, two found that the workplace and workplace neighbourhood were substantial contributors to MVPA, but much of this was likely owed to transportation to-and-from work and daily time spent at work.71,74 Interestingly, Troped et al.78 found most MVPA occurred outside of home and work buffers than within them.

Three studies conducted sex-specific analyses. Troped et al.78 found no significant differences in the location of MVPA by sex. Hillsdon et al.67 found that men accrued significantly more PA outside of the neighbourhood than women (64.7 % vs. 57.4%). Dewulf and colleagues65 found that among men, greater time spent in non-green areas was associated with more MVPA; the opposite was true in women.

Discussion

This rapid review examines and synthesizes the available literature around locations of PA and ST in children, youth and adults. Findings provide guidance for the design of future studies by understanding where individuals engage in PA and ST and areas of uncertain/weak evidence. Results can be used to support the current knowledge base around correlates and determinants of PA and ST and subsequently inform direction for new interventions by identifying environmental settings of importance.

Only one other review to date has looked at location-based studies. McGrath et al.8conducted a systematic review of objectively measured environmental features and MVPA in children and youth. They found that walking on local streets accounted for the greatest proportion of children and youth’s daily activity spent outdoors (~40%). They also found that a large proportion of PA occurred in non-green space/other urban areas (26-27%). Similar to our results, they found that streets, roads, car parks, hard surface play areas, pedestrian pathways and shopping areas contributed more to outdoor PA than green spaces, parks and other grassland areas.8 Our results also underscore the importance of active transportation toand- from schools and schoolyards as major contributors to daily PA levels in children and youth. Important to note, however, is that McGrath et al.8 excluded studies which examined citywide data rather than that of neighbourhood areas or data that used school locations as proxies for residential neighbourhoods. Our review builds on this previous work by including: studies regardless of type of location; other intensities (LPA, ST); updated literature; and, adults.

Findings of the present review support and contrast previous systematic reviews looking at the correlates and determinants of PA. The evidence for associations between aspects of the built environment and PA has been mixed, but with the most consistent evidence derived from studies using objectively measured environments and domain-specific PA.80 In children and youth, evidence suggests a positive association exists between access to recreation facilities, playgrounds/parks, measures of walkability (including sidewalks) and PA.80,81Findings from our review suggest that schoolyards and active transportation are substantial contributors to child/youth daily PA rather than parks, especially on weekdays. Similar to our findings, systematic review evidence suggests that distance to school is negatively associated with PA in children.81

In adults, systematic review evidence suggests that in general, access to recreation facilities is positively associated with PA.80,82,83 Only one68 of the location studies used in our review commented specifically on indoor recreation facilities (e.g., fitness centres, pools). There is mixed evidence on the association between sidewalks and PA.82,83 Among adults, factors in the built environment are likely relevant to different domains of PA. For example, sidewalks may be integral to the active transportation environment or to the workplace environment. Similar to our findings, evidence also suggests that the transportation environment is a correlate and determinant of total PA in adults.80

Much less previous work has examined the associations between factors in the built environment and ST.9,84,85 In children, contrary to popular assumption, a higher playground density and availability of sports equipment in the school has been shown to be associated with greater ST,85whereas increasing the length of breaks at school and providing safe road crossings are associated with lower ST.85 The studies in our review highlight the impact of the school environment on ST. For instance, most ST is recorded in the home and school environments,23 emphasizing the importance of activity breaks in these environments and providing an opportunity for active transportation to-and-from school for regular MVPA. In adults, evidence suggests that proximity or density to green spaces is negatively associated with objectively measured sitting time.84 Only one study in the present review looked at a measure of area ‘greenness’ and found that ST was higher in nongreen areas compared to greener areas.65Mixed findings have been found around the association with neighbourhood walkability, walking/cycling infrastructure and recreation facilities and ST.9,84 While the presence of active transportation supportive environments (e.g., lockers, bike storage, shower facilities) in the workplace have been shown to be positively associated with total objectively measured ST, they are also associated with greater levels of PA.84 This finding suggests and supports the idea that interventions designed to increase PA may not always result in significant reductions of ST.86

This review serves to provide direction for future location-based studies. Many of the studies did not employ a full-day perspective and instead reported on results related to specific locations. For example, many focussed exclusively on time spent in travel to-and-from school or work. In recognition of the importance of movement across the 24-hour spectrum, future studies should report on locations across all intensities of movement including LPA and ST. Future studies would also benefit from reporting results by sex to understand if girls/women and boys/men spend their time in different locations at different intensities.

Strengths and limitations

The strengths of this review include a comprehensive search strategy developed with two research librarians, an a priori established protocol and the assessment of risk of bias. The review also took a lifecourse approach by looking at the findings separately in children, youth and adults and reporting on sex differences where available. Unfortunately, none of the included studies reported on findings specifically in older adults. Given that many included this population in their overall sample, we encourage future researchers to report on this segment of the adult population separately.

One of the major limitations of the review is the heterogeneity of the studies and their reporting. There was little standardization of the nomenclature used to describe the locations and many studies did not report measures of variance, preventing the conduct of a meta-analysis; future studies would benefit from reporting both on daily minutes and proportion per location. We were also not able to distinguish whether home environment behaviours occurred inside or outside of the home. Nor were we able to discern the location characteristics (e.g., road, path, and sidewalk) for many studies that focussed on active transportation. As this is an important domain of PA, we felt it was important to include these studies under a general “active transportation” location. Other studies reported movement behaviours in locations often associated with active transportation (e.g., roads), but the purpose/domain of this activity was not distinguishable. There will always be a limitation with being too specific in these efforts as active transportation takes place over a heterogeneous set of street geographies. As an example, it might start on a quiet residential street, continue on a shared-use walk/bike path, move to a painted bike lane and finish on a dedicated bike lane. In this example, only 3 out of 4 components of the journey occurred on a “road”, and even then the types of roads differ. In our opinion, the key point is that PA occurred in the “travel” environment. Many of the studies were based on small and biased samples; there is a need for larger representative samples. Using GPS overlaid onto GIS helps to increase the accuracy of identifying locations of movement, but it is important to understand that the quality of GIS data can be variable and can ultimately introduce a source of measurement bias.87 Findings from the literature have also identified that 12-14 days of monitoring are needed to provide reliable estimates of PA, and that time in the home or commercial environments require substantial monitoring times (> 19 days).88,89 The majority of the included studies assessed movement over a 7-day period and many only required 4 days of valid data. Therefore, the findings may not be reliable. Future studies should consider the evidence around monitoring time requirements for reliable estimates. There was also substantial heterogeneity in the measures of activity and ST including the different devices, wear time requirements and cut-points used to define intensity. Finally, while GPS devices improve our understanding of the location of PA and ST, they also have their own limitations: there is the potential for large data loss due to signal drop outs, inadequate battery power and wear time adherence.16Many of the studies experienced substantial data loss.

Conclusion

In conclusion, this review provides a summary of the evidence around the locations where children, youth and adults obtain their ST, LPA and MVPA. There is limited evidence around the location of LPA and ST compared to MVPA. Evidence suggests that the active transportation environment is a potentially important contributor of MVPA across an individual’s lifespan. There is a need for future location-based studies to report on locations of all intensity of movement using a whole-day approach in larger more representative samples.

Acknowledgements

We would like to thank Katherine Merucci from the Public Health Agency of Canada (PHAC) Health Library and Nathalie Leclair from the Berkman Library at the University of Ottawa Heart Institute for their help with the search strategy development. We would also like to thank Alexandria Melvin for her assistance with data verification. Stephanie Prince is funded by a Canadian Institutes of Health Research – PHAC Health System Impact Fellowship.

Conflicts of interest

We declare that we have no conflicts of interest related to this work.

Authors’ contributions and statement

SAP was responsible for the conceptualization, design, acquisition, analysis, interpretation of the data, and drafting and revising of the paper. GPB, DPR and WT were responsible for the conceptualization, interpretation of the data, and revising of the paper.

The content and views expressed in this article are those of the authors and do not necessarily reflect those of the Government of Canada.

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