Scholarly article on topic 'Built environmental correlates of physical activity in China: A review'

Built environmental correlates of physical activity in China: A review Academic research paper on "Social and economic geography"

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Abstract of research paper on Social and economic geography, author of scientific article — Kristen Day

Abstract Objective China faces growing levels of physical inactivity and obesity, associated with increasing urbanization and changing lifestyles in recent years. China is expanding its cities to accommodate a growing urban population. This paper identifies built environment factors that are associated with physical activity in China. Findings can inform urban design and development in China to support increased physical activity. Methods This paper is modeled on a review of built environment correlates of walking by Saelens and Handy (2008). Saelens and Handy reviewed research in developed countries. The present paper reviews 42 empirical studies that were conducted in China and were published between 2006 and 2014. Results Results discuss the association of built environment features and physical activity for transportation, recreation and work. Studies focus on adults and on major cities. Data on the built environment is typically self-reported. Strongest evidence was found for the positive association of physical activity with proximal non-residential locations, pedestrian infrastructure, aesthetics, and non-park physical activity facilities, and for the negative association of physical activity with urban residence. In terms of physical activity for transportation, evidence is strongest for associations between physical activity for transportation and proximal non-residential locations. Conclusion More research is needed on the built environment and physical activity, especially including research on significant features of Chinese cities, such as air pollution, high density levels, traffic safety, and others. Research on associations between built environment features and physical activity should consider the specific social and built environment contexts of Chinese cities.

Academic research paper on topic "Built environmental correlates of physical activity in China: A review"

Review Article

Built environmental correlates of physical activity in China: A review

Kristen Day

Tandon School of Engineering New York University, Brooklyn, NY 11201, United States

ARTICLE INFO

Article history:

Received 21 October 2015

Received in revised form 13 January 2016

Accepted 11 March 2016

Available online 15 March 2016

Keywords: China

Physical activity Environment Transportation Recreation

ABSTRACT

Objective. China faces growing levels of physical inactivity and obesity, associated with increasing urbanization and changing lifestyles in recent years. China is expanding its cities to accommodate a growing urban population. This paper identifies built environment factors that are associated with physical activity in China. Findings can inform urban design and development in China to support increased physical activity.

Methods. This paper is modeled on a review of built environment correlates of walking by Saelens and Handy (2008). Saelens and Handy reviewed research in developed countries. The present paper reviews 42 empirical studies that were conducted in China and were published between 2006 and 2014.

Results. Results discuss the association of built environment features and physical activity for transportation, recreation and work. Studies focus on adults and on major cities. Data on the built environment is typically self-reported. Strongest evidence was found for the positive association of physical activity with proximal non-residential locations, pedestrian infrastructure, aesthetics, and non-park physical activity facilities, and for the negative association of physical activity with urban residence. In terms of physical activity for transportation, evidence is strongest for associations between physical activity for transportation and proximal non-residential locations.

Conclusion. More research is needed on the built environment and physical activity, especially including research on significant features of Chinese cities, such as air pollution, high density levels, traffic safety, and others. Research on associations between built environment features and physical activity should consider the specific social and built environment contexts of Chinese cities.

© 2016 The Author. Published by Elsevier Inc. This is an open access article under the CC BY-NC-ND license

(http://creativecommons.org/licenses/by-nc-nd/4.0/).

Contents

1. Introduction............................................................................................................................303

2. Methods ..............................................................................................................................304

3. Results................................................................................................................................305

3.1. Active living research in China....................................................................................................305

4. Discussion and conclusions..............................................................................................................305

Conflict of interest ..........................................................................................................................315

Transparency Document......................................................................................................................315

Acknowledgments ..........................................................................................................................315

References..................................................................................................................................315

1. Introduction

Rising obesity, declining physical activity, and growing rates of chronic disease are major concerns in China and in other developing countries. According to the World Health Organization (WHO) (2015), 36.2% of adults in China are now overweight and 5.9% are obese. Nearly

E-mail address: kday@nyu.edu.

80% of deaths in China are attributable to noncommunicable (or chronic) disease (World Health Organization, 2005). Between 1991 and 2006, the average weekly rate of physical activity dropped by approximately 32% among adults (Ng et al., 2009). For men, self-reported occupational, domestic, transportation, and leisure physical activity, fell from 350 MET (metabolic equivalent) hours per week in 1997 to 253 MET hours per week in 2006. Women's physical activity declined from 390 MET hours per week in 1996 to 246 MET hours in 2006 (Ng et al.,

http: //dx.doi.org/10.1016/j.pmedr.2016.03.007

2211-3355/© 2016 The Author. Published by Elsevier Inc. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).

2009). Insufficient physical activity is a leading contributor to diseases such as diabetes, cancer and cardiovascular disease (WHO, 2015).

To reduce obesity and overweight and to combat noncommunicable diseases, the World Health Organization advocates strategies that target entire populations, including the design of environments to promote physical activity for transportation and recreation as part of everyday life (WHO, 2015), or "active living." Historically, research on active living has examined developed countries, especially the USA and Canada, Australia, European countries, and Japan. Active living research from developed countries is not necessarily generalizable to developing countries such as China, where the cultural context and the built environment may differ (Sallis, 2011). Indeed, physical activity in China is shaped by specific built environment factors and also by Chinese cultural norms surrounding physical activity, health, and travel (for an overview of cultural factors, public policies, and current urban planning practices that affect physical activity levels in China, see Day et al., 2013).

The design of Chinese cities to promote physical activity is a timely issue. China is expanding its cities at a rapid rate to accommodate enormous growth in its urban population—including an additional 200 million residents between 1990 and 2000 (The State of China's Cities,

2010). Accommodating this population could require an estimated 170 new mass-transit systems, 5 billion square meters of road, and 40 billion square meters of new floor space. Though the rate of development may slow in China's current economic situation, it is important to understand the links between the built environment and physical activity to help inform these extensive city building efforts.

This paper reviews existing research on the relationship between the built environment and physical activity in China. It identifies what is known so far, suggests key questions for future research, and highlights some potential differences in the relationship between the built environment and physical activity in China compared to research findings from developed countries.

2. Methods

This paper reviews 42 published empirical studies on physical activity and the built environment in China. The paper is modeled closely on a paper by Saelens and Handy (2008). Saelens and Handy (2008) are widely cited—701 times as of July 6,2015, according to Google Scholar. Saelens and Handy (2008) reviewed 13 published literature reviews and 29 empirical research reports on the association between walking and the built environment. Their paper offers a systemic framework for analysis of literature that is replicable and that, importantly, allows for comparison with the present review. Saelens and Handy's (2008) review provides a guide for the organization of this paper and for the methods of analysis. Note that Saelens and Handy (2008) review studies from developed countries only (reflecting the available literature at that time). They focus exclusively on walking. The present paper, in contrast, reviews studies from China only and includes research on various types of physical activity, including walking and others.

For the present paper, a systematic search was conducted to identify studies published on the association between the built environment and physical activity in China. Search terms used in Web of Science (science and social science) included "physical activity," "walk," "bicycle," "bicycling," "travel," "transportation," "exercise," "recreation," "mode share" AND "environment," "park," "sidewalk," "trail," "mixed use," "urban," "suburban," "urban design," "walkability," "walkable," "bike-friendly," AND "China." Additional search terms included "active living," "active design," "walkability" AND "China." Search terms used for this analysis were those identified by Saelens and Handy (2008), plus additional terms to include non-walking physical activity and to narrow the focus to China. A few search terms used by Saelens and Handy (2008), including environment, design, and neighborhood, were not included because these terms were overly broad for this analysis. Bibliographic lists prepared by the Robert Wood Johnson Active Living Research

program from 2002 through 2011 were also searched, as was the Active Living Research program's list of research studies from outside of the USA. The reference lists of several published literature reviews on the built environment and physical activity were reviewed to identify studies on China. Finally, the reference lists for all studies that were included in this paper were reviewed to identify possible studies for inclusion.

Each study that as included in this paper met the following criteria: (1) published as a full paper (not only an abstract); (2) included a primary report of methods, analysis and findings; (3) published in a peer-reviewed journal; (4) included an examination of the association between the objective and/or perceived built environment and physical activity; (5) included research that was conducted (all or in part) in China; (6) published before or during 2014; and (7) written in English. Because of the focus of this paper on implications for planning and design of the built environment to support physical activity, studies that examined only the social, cultural or economic environment, were not included (as in Saelens and Handy, 2008). The built environment was defined broadly, and included concepts such as urban versus rural distinction, natural environment features, and also population density, which impacts transportation planning.

Studies were reviewed using a preliminary coding scheme based on Saelens and Handy (2008). The coding scheme specified factors such as year of publication, built environment data sources, built environment factors examined, and geographic unit of analysis. Twenty studies were reviewed using the preliminary coding scheme. Based on the review of the first 20 studies, the coding scheme was revised to include additional factors, such as disciplinary orientation of authors and additional types of physical activity (for work as well as for recreation and transportation). All studies were reviewed again using the revised coding scheme.

Review procedures included the following. Each study was characterized in terms of the country in which the data were collected, sample, built environment factors, geographic unit of analysis, type of physical activity, covariates, and major results. Studies were also coded in terms of methods used to collect data (e.g., survey, interview, observation) and on whether environmental data were objective or perceived. (For perceived environmental factors, data on the environment was provided by respondents themselves through self-report.) Studies were further characterized in terms of their geographic unit of analysis. This information was often vague. (The same was true in Saelens and Handy (2008).) Studies were further coded in terms of the types of environmental factors examined, and the environmental scale ofthe study (micro, meso or macro). As in Saelens and Handy (2008), micro-environments referred to the environments immediately around where an individual lives (or works or goes to school, for studies of workplaces or schools). Individuals who live on the same street could potentially vary in their micro-environments. Meso environments included the small scale environments in which an individual lives, such as a neighborhood or census block group. Macro-environments were the larger scale environments in which an individual lives, such as the city or county. All individuals within that scale are considered to have the same environment.

The review also identified the type(s) of physical activity measured (recreation, transportation, work, and/or general); and whether results were expected, unexpected, and null. Expectedness was based on prior empirical research and conceptual models on the relationship between the built environment and physical activity. "More" of the following built environment factors were expected to be associated with more physical activity: density; proximity to nonresidential land uses (includes mixed land uses, transit access); street connectivity; parks and open/green space (quality and availability); non-park physical activity facilities; pedestrian infrastructure (presence and condition); bicycle infrastructure (presence and condition); traffic safety; aesthetics (including cleanliness). "Less" of the following built environment factors were expected to be associated with more physical activity: distance to specific non-residential land uses; crime; traffic volume and noise; high

temperatures or oppressive weather conditions; pollution and emissions; and stray animals. Existing literature in developing countries links urban residence with higher obesity and lower levels of physical activity (c.f., Andegiorgish et al., 2012; Muntner et al., 2005; Ramons de Marins et al., 2002), so urban location was also expected to be associated with less physical activity. As noted earlier, the existing literature focuses heavily on developed countries. The discussion section addresses where relationships in China differ from what is "expected" according to existing literature. For ease and because the current literature does not permit greater specificity, "expectedness" was considered the same for physical activity for recreation, transportation, work, and general. For built environment factors that were measured but for which significant or nonsignificant findings were not reported, the relationship with physical activity was characterized as "null." Finally, studies were coded in terms of which factors, if any, were included as co-variates.

3. Results

3.1. Active living research in China

A total of 42 empirical research reports were identified that were published before or in 2014 (see Table 1). The earliest identified studies were published in 2006 (Li et al., 2006; Shi et al., 2006). Rate of publication increased modestly over time, to a total of nine studies published in each of2013 and 2014. Papers are treated as discrete studies. Note that in some cases, a single study may have produced multiple papers. In terms of disciplinary orientation of authors (as identified by each author's academic department or professional affiliation), health-related disciplines (including public health, medicine, epidemiology, and others) were most well represented, with 21 papers having one or more authors from a health-related discipline. Urban planning-related disciplines were also common (including architecture, urban design, etc.). Research by investigators in sports and exercise-related fields was also well represented (see Fig. 1). Multidisciplinary research was common; almost half the studies included authors from more than one field.

Most research focused on China only. A small number of studies included China and one or more additional countries. Much of the research was conducted in China's largest cities: Hong Kong, Beijing, Shanghai, and others. Most studies examined adults.

Most studies included both men and women participants. (A few studies did not report participants' gender.) Most studies in this paper examined adults. Smaller numbers of studies examined seniors (age 65 and older) and children (under age 18). Only studies that explicitly noted that they included adults over age 65, were characterized as including seniors. Thirteen studies explicitly included seniors (over age 65), but only six studies reported results separately for seniors. Five of these six studies reported associations between nearby nonresidential locations and physical activity among seniors. Nine studies included children under age 18; only six studies reported results separately for children. There was no consistent support for specific associations between the built environment and physical activity among children.

The most common method for collecting data on built environment characteristics was by survey or interview (see Table 2). Such built environment data was self-reported rather than objectively observed. Fewer studies used observation or environmental audit or GIS (Geographic Information System) as a source of data on built environment characteristics. For physical activity data, several studies used the IPAQ (International Physical Activity Questionnaire, 2009) or modified IPAQ. Most studies used another survey or interview, often created for the study itself. Only two studies used accelerometers to collect physical activity data. Studies examined transportation-related physical activity (21 studies) and recreation-related physical activity (12 studies).

Sixteen studies examined "general" physical activity that was not further specified by purpose. Four studies examined physical activity for work.

As in Saelens and Handy (2008), individual level demographic variables were a common co-variate and were included in the multi-variate analyses for most studies. Other co-variates varied (e.g., attitudes about the environment and health status). In contrast with Saelens and Handy (2008), most research in China investigated environmental factors at the meso scale (e.g., neighborhood) rather than at the micro-scale (the physical environment immediately radiating from where an individual lives) (see Table 2). This distinction reflects how built environment data were collected in research in China, which was most often through participants' self report about their neighborhoods. In contrast, in the studies in developed countries reviewed by Saelens and Handy (2008), built environment information was frequently generated through GIS data linked to individual residences.

Table 3 summarizes the built environment features that are associated with physical activity for transportation, recreation, work, and general, in terms of whether results are expected or unexpected (as in Saelens and Handy, 2008). Individual studies may contain results tied to more than one type of physical activity, and may include results that are both expected and unexpected. Studies with results for composite measures of the built environment are assigned to each relevant built environment feature in this table and also noted as "composite."

Built environment features were considered in terms of their associations with specific types of physical activity (transportation, recreation, or work). Physical activity for transportation was examined in 21 studies. Evidence is strongest for associations between physical activity for transportation and proximal non-residential locations. Twelve studies examined physical activity for recreation. Evidence supported the association between physical activity for recreation and proximal non-residential locations and non-park physical activity destinations. Only four studies examined physical activity for work, so these findings were not conclusive.

4. Discussion and conclusions

This review included a limited number of studies overall, and all built environment features were not included in all studies. At this stage, one cannot speak definitively of the associations between physical activity and specific built environment in China. Some conclusions can be made, however, by considering the overall number of times a variable was studied and the percentage of studies that found positive associations. Studies in this review provided most support for the association between physical activity and proximal non-residential locations, pedestrian infrastructure, aesthetics, and non-park physical activity facilities, and for the negative association of physical activity with urban residence. Findings also suggested an association between physical activity and parks/open space and bicycling facilities, though only a small number of studies examined these factors. Findings also supported associations between composite features and physical activity, though the type of environment defined by "composite measures" varied somewhat. Findings were mixed on the association between physical activity and distance to specific non-residential land uses, network characteristics, crime safety, traffic safety, and density. Only one or two studies examined the association between physical activity and the presence of stray animals, weather/temperature, and pollution, so these findings are inconclusive.

In their meta-analysis of literature reviews on the built environment and walking, Saelens and Handy (2008) find strongest support for associations between walking for transportation and density, distance to nonresidential destinations, and land use mix. Their findings on built environment features linked to recreational walking were less conclusive. The present study focuses on all forms of physical activity, not only walking, and it deals with 42 studies (total) and not the large number of studies covered by Saelens and Handy (2008). Still, it is worth

Characterization of studies by country, sample, environmental factors and data source, geographic unit of analysis, type of physical activity and how measured, covariates, and major results. Results are reported for findings that are statistically significant, typically at P < 0.05 but occasionally at P < 0.10. When multiple models were included in the articles, the most complete model result was considered (as in Saelens and Handy, 2008).

Reference

Country1

Sample

Environmental factors, data source2

Environmental factors examined

Analyzed geographic

Physical activity type/physical activity

Covariates3 Results

Adams et al. (2013)

Aldinger et al. (2008)

Alfonzo et al. (2014)

China, Belgium, Brazil, Canada, Columbia, Japan, Lithuania, New Zealand, Norway, Sweden, USA

An and Zheng China (2014)

11,541 adults aged 18 to 64 in Hong Kong

Survey, interview

Residential density; access to shops/services, public transit, and recreational services; sidewalks; bike paths; personal safety from

Neighborhood

191 administrators, teachers & staff, students, parents from elementary, middle, junior high, high, & vocational schools in Zhejiang Province 853 adults in Hangzhou, Shanghai

Qualitative description of physical environment

Survey

2532 respondents from urban areas and 1784 respondents from rural areas in 10 provinces

Composite description of intervention: schools improved facilities such as dining rooms, dormitories, teaching and sports facilities, enhanced cleanliness and did beautification projects [intervention also includes non-physical environment changes.] Density/building height, proximity/land use mix, connectivity, form, parks and public space, pedestrian infrastructure/amenities, bike infrastructure/amenities, personal safety, traffic safety, aesthetics, recreational facilities. Perceived neighborhood convenience for walking

Observation/environmental Time to walk to nearest exercise facility audit

Distance to

exercise

facility

Bauman et al. China, Australia, 142,693 (China), 6763

Survey

(2011)

Bosdriesz et al. (2012)

Fiji, Malaysia,

Nauru,

Philippines

China and 37

additional

countries

(Fiji), 2572 (Malaysia), 2085 (Nauru), 3307 (Philippines)

non-institutionalized adults aged 18-64 living in private dwellings

177,035 adults aged 18 to 69

Urban vs. rural residence (only measured for Urban area China, Fiji, Malaysia and Australia). Definition of urban based on level of economic development (China)

Climate temp web site of world temperatures, World Bank Database, CIA World Factbook

Average yearly temperature in capital city, percentage of rural population, economic development (GDP).

Country

Transportation and recreation/IPAQ or modified IPAQ

School

Neighborhood

General (not specified)/survey or interview

Transportation and recreation/survey or interview

Demos, other

Recreation/accelerometer Demos

General (not specified)/survey or interview

General (not specified)/IPAQor modified IPAQ

(1) Residents in activity supportive neighborhoods more likely to meet guideline for overall physical activity. (2) Residents in high walkable and unsafe neighborhoods with few recreation facilities more likely to meet guideline for total physical activity and for walking.

(3) Residents in dense neighborhoods with transit and shops with few amenities less likely to meet guideline for total physical activity.

(4) Respondents in overall activity supportive neighborhoods more likely to meet guideline for walking.

Enhanced schools were associated with increased physical activity for some participants.

(1) Respondents in neighborhoods with higher walkability more likely to spend more time walking for commuting, non-commuting, and exercise, and on overall walking, compared to respondents in neighborhoods with below average walkability. (2) Respondents who believe neighborhood's built environment was less convenient for walking, spent more time walking overall and more time walking for non-commuting purposes. (1) Individuals in 10 min walking distance to exercise facility more likely to have some leisure time physical activity. (2) Rural residents aged 18 or older less likely to have leisure time physical activity, compared to urban residents. (3) Association between proximity to exercise facility and leisure time physical activity greater for women than for men. (4) Association between proximity to exercise facility and leisure time physical activity greater for working age adults than for older adults. (5) Association between proximity to exercise facility and leisure time physical activity greater for those with college or graduate degree. (6) Association between proximity to exercise facility and leisure time physical activity greater for urban dwellers. (1) Residents of urban areas more likely to be active during leisure time compared to rural populations. (2) Residents of urban areas were less likely to be active in work, compared to rural population (3) Men living in urban areas engage in less walking or cycling for commuting, compared to rural residents (1) Negative association between GDP and physical activity. (2) Higher average daily temperature associated with less physical activity. (3) Lower percentage of rural

Cerin et al. (2012a)

484 Chinese speaking elders with no cognitive impairment and able to walk without assistance in 32 communities in Hong Kong

Survey

Cerin et al. (2012b)

Cerin et al. (2013a)

484 elders age 65 +, from 4 elderly health centers in 4 catchment areas in Hong Kong

Survey

484 elders able to walk unassisted, living in 32 neighborhoods in Hong Kong

Cerin et al. (2013b)

484 elders with no diagnosed cognitive impairment who can walk unassisted and live in 32

Perceived availability of destinations (land use mix- diversity, land use mix-access to shops, access to public transport); accessibility and pedestrian infrastructure (street connectivity, infrastructure for walking, indoor places for walking, physical barriers to walking); easy access to residential entrances; residential density; crowdedness; personal safety (presence of people, crime); traffic and road hazards; availability of sitting

Neighborhood

Transportation/IPAQ or modified IPAQand survey or interview

Perceived: residential density, land use mix, Individual

street connectivity, infrastructure for walking, respondent

indoor places for walking, aesthetics, presence

of people, crowdedness, traffic and road

hazards, traffic speed, social disorder/littering,

crime, pedestrian infrastructure, ease of

residential entrance, sitting facilities

Recreation/IPAQ or modified IPAQ

Observation/environmental audit

Recreation and commercial destinations (pool, gym/fitness center, community/senior center, playground, sports field, commercial facilities); infrastructure facilities (public facilities, path quality, path obstructions, indoor/covered walking places); safety (crime, traffic, pedestrian safety, stray animals); aesthetics and cleanliness, including pollution

Neighborhood

Recreation/IPAQor modified IPAQ

Observation/environmental audit

Public transit points; recreational facilities; places of worship; health clinics; government/public facilities; entertainment facilities; non-food retail and services; food

Neighborhood

Transportation and recreation/IPAQ or modified IPAQ and survey or interview

population (higher urbanization) associated with less vigorous and less moderate physical activity.

(1) Perceived land use mix-diversity, access to shops, physical barriers to and infrastructure for walking, crowdedness, traffic and road hazards, easy access to residential entrances and sitting facilities in neighborhood associated with frequency and/or weekly minutes of within-neighborhood walking for transport.

(2) Perceived land use mix-diversity, access to shops, infrastructure for walking, crowdedness, easy access to residential entrances and sitting facilities in neighborhood, perceived access to public transport and dwelling density associated with measures of overall transportation-related walking. (3) Access to shops, crowdedness, easy access of residential entrance, infrastructure for walking, presence of sitting facilities associated with overall and within-neighborhood walking. (4) Access to public transport associated with overall walking. (5) Land use mix-diversity and physical barriers to walking associated with within-neighborhood walking.

(1) Perceived bridge/overpass connecting to services associated with overall recreational walking. (2) Perceived proximity to recreational facilities, infrastructure for walking, indoor places for walking, presence of bridges/overpasses connecting to services associated with within-neighborhood recreational walking.

(1) Parks, signs of crime/disorder, building attractiveness, noise/air pollution associated with walking for recreation. (2) Public facilities (sitting,toilets), indoor/covered places for recreation, natural sights, noise/air pollution, litter associated with nonparticipation in walking for recreation.

(3) Path quality, traffic load, noise/air pollution associated with leisure time activity other than walking (OLTPA). (4) Outdoor sports fields, senior center, park, public facilities, sign of crime/disorder, traffic load, trees associated with nonparticipation in OLTPA. (5) Path quality, pollution moderated associations of odds of non-participation in OLTPA with playground, park and pool.

(6) Stray animals moderated associations of odds of non-participation in OLTPA on parks, playground. (7) Signs of crime/disorder moderated associations of odds of non-participation in OLTPA on park, sport field. (8) Availability of public facilities moderated associations of odds of non-participation in OLTPA with parks.

(1) Signs of crime/disorder positively associated with overall walking and with within-neighborhood walking for transport.

(2) Prevalence of streetlights positively

Reference Country1

Sample

Environmental factors, data source2

Environmental factors examined

Analyzed Physical activity

geographic type/physical activity unit measure

Covariates3 Results

Cerin etal. (2013b)

neighborhoods in Hong Kong

Cerin et al. (2014)

Ding et al. (2013)

Feng et al. (2014)

China, Belgium, Brazil, Columbia, Czech Republic, Denmark, Mexico, New Zealand, Spain, UK, USA

China, Belgium, Brazil, Canada, Columbia, Japan, Lithuania, New Zealand, Norway, Sweden, USA

6968 adults in 16 city regions in 12 countries

11,541 adults age 18 to 65, living in towns in Hong Kong with populations >30,000

Survey

3894 adults in 8 districts in Nanjing

Survey, interview

Survey

Jiang et al. (2012)

2155 BRT users in Jinan, including 1233 with information on distance

GIS, interview

and grocery stores; restaurants; safety; infrastructure (path obstructions, good path conditions, sloping street); public services

Perceived residential density, land use mix-diversity, land use mix-access, street connectivity, infrastructure and safety for walking, aesthetics, traffic safety, safety from crime, streets having few cul-de-sacs, no physical barriers to walking

Main type of housing in neighborhood as measure of residential density (not calculated for Hong Kong); access to shops; presence of transit stops; presence of sidewalks, bicycle facilities, free or low cost recreation facilities; crime

Neighborhood

Neighborhood

General (not specified)/accelerometer

General (not specified)/IPAQor modified IPAQ

Population density, accessibility, distance to nearest metro station, housing type

1000 m area Transportation and around recreation/survey or

Transportation interview Analysis Zone (TAZ)

Protection (security against traffic safety risk and crime); comfort (ease of walking, including sidewalk quality, street

Length of walk to BRT station, 600-m buffer

Transportation/survey or interview, GIS analysis of distance walked

associated with within-neighborhood walking for transport. (3) Prevalence of stray animals negatively associated with within-neighborhood walking for transport. (4) No significant association between pedestrian safety, sloping streets, public facilities, path obstructions, or good path conditions AND walking for transport or overall walking. (5) Prevalence of public transit points and diversity of recreational destinations associated with weekly minutes of overall walking for transport. (6) Health clinic/service and place of worship, higher diversity in recreational destinations, and greater prevalence of non-food retail and services, food/grocery stores, and restaurants in neighborhood were predictive of more within-neighborhood walking for transport. (7) Prevalence of public transit points in safe neighborhoods (only) associated with overall walking for transport. (8) Diversity of recreational and entertainment destinations in safe neighborhoods (only) associated with within-neighborhood walking for transport. (9) Composite destinations indices associated with walking for transport.

(1) Perceived aesthetics and land use mix-access were significant predictors of weekly minutes of MVPA and meeting PA guidelines for cancer/obesity prevention.

(2) Perceived environment had beneficial effect on probability of meeting PA guidelines for cancer and weight gain prevention in Hong Kong.

(1) Shops near home, transit stops near home, sidewalks, bicycling facilities, and free or low cost recreational facilities associated with higher odds of meeting physical activity recommendations. (2) Crime-related safety associated with lower odds of meeting physical activity recommendations.

(1) High population density associated with greater levels of walking or cycling to work.

(2) Accessibility of employment not associated with mode choice for commuting trips. (3) Housing type has strong impacts on mode choice for commute and shopping-leisure trips: those in former danwei housing use non-motorized transport more than do people in commodity housing.

(4) Population density, distance to nearest metro station have no significant impact on mode choice for shopping-leisure trips.

(5) Higher densities of shopping-leisure facilities associated with increased walking trips, compared to public transport trips. (1) Integrated boulevard Bus Rapid Transit (BRT) corridor stations (poor protection, average comfort, good enjoyment, good

walked to BRT station cleanliness); enjoyment (aesthetic and

utilitarian aspects tied to presence of activities, relief from elements); directness (relative detour factor)

Li et al. (2006) China 1787 adolescents aged Survey, survey of school Recreational facilities in the community,

11-17 attending junior environment by school places around the home to play, high schools in Xi'an City doctor transportation, level of residence, safety

concern, household facilities for playing games, school environment

Li et al. (2014) China

Monda et al. (2007)

497 dyads of parents and Survey children in 4 primary schools in Guangzho and Hechi

8760 adults Survey

Parents' perceived walkability of their neighborhood environments (types of residences, types of other facilities, access to services, distance to facilities, safety from traffic, aesthetics, safety from crime, street qualities, presence of cul-de-sacs, barriers, hilly)

Level of urbanization

Naess (2009 ) China, Denmark

28 interview respondents, 3000 + survey respondents who are residents in 5 areas in Hangzhou

Survey

Type of residence, workplace/school location, location of activities, distance to downtown and local centers

Naess (2010) China

Naess (2013) China

28 interview respondents, 3154 survey respondents age 15 or older in 40 residential areas in Hangzhou (242 respondents from other areas)

28 adults living in 5 regions in Hangzhou

Survey, interview

Residential distance from central city and distance from residence to second- and third-order center

Distance to destinations (linked to residence in inner city vs. suburbs); perceived conditions of route (traffic safety, congestion)

surrounding BRT stations

Home, area Transportation and near home, recreation/survey or community interview

Demos, other

Neighborhood Recreation/survey or interview

Demos, other

directness) associated with longer walking distance, compared to arterial edge BRT corridor stations (poor protection, good comfort, poor enjoyment, poor directness) and compared to below expressway BRT corridor stations (poor protection, poor comfort, average enjoyment, good directness). (2) Terminal stations have longer distance walked and transfer stations have shorter distance walked, compared to typical stations. (3) Density concentrated near BRT station associated with shorter distance walked. (4) Density lower near BRT station associated with longer distance walked, compared to area away from station. (5) Stations located farther from city center associated with longer distance walked. (1) Access to public facilities, concerns about neighborhood safety associated with inactivity. (2) Adolescents living in a house without sidewalks were more inactive.

(3) Living in areas without nearby vacant fields and unavailability of video games near home associated with inactivity for boys.

(4) Greater inaccessibility of public facilities and lack of sidewalks near home associated with inactivity in girls.

No association between perceived environmental factors and children's daily moderate to vigorous physical activity level.

Community Work/survey or Demos interview

Community Transportation/survey or Demos,

interview other

Community Transportation/survey or Demos, interview other

Increased urbanization associated with decreased occupational physical activity for men and women.

(1 )Those who lived near city center have longer average travel distance by non-motorized modes. (2) Living close to city center associated with greater likelihood of non-motorized travel, but with shorter non-motorized travel distances; and with higher proportion of total travel distance through non-motorized modes. (3) Living near second order center associated with higher likelihood of using non-motorized modes. (4) Living near third order center associated with somewhat higher likelihood of non-motorized modes; and with somewhat higher proportion of total traveling distance during weekends by non-motorized modes. The closer to city center residents live, the higher their proportion of travel on foot and/or by bicycle.

Individual Transportation/survey or None respondent interview

(1) Shorter distance to destination, increased traffic congestion, and fewer parking spaces associated with increased likelihood of active travel. (2) Bad weather and concern for traffic

Reference Country1 Sample Environmental factors. Environmental factors examined

data source2

Naess (2013)

Ng et al. 2009 China 58,112 adults Survey, data from local area Level of urbanization represented by

administrators and official infrastructure development over time, records including population, density, access to

markets for household goods, transportation, educational institutions, health facilities, sanitation and housing infrastructure

Pan et al., (2009)

1709 individuals in 4 neighborhoods in Shanghai

Observation/ environmental audit, census, GIS

Design differences in neighborhoods from different times (1930's-60's traditional, 1970's-80's planned community, late 1980's private sector). Differences include distance to CBD, land use mix, human scale, residential building height, road width, street pattern, population density, road network density, block size, transit availability

Pan et al. (2010)

900 individuals at 4 transit stations in Shanghai

Survey

Distance to destination, transit station; availability of bike parking

Sallis et al. (2009)

China, Belgium, Brazil, Canada, Columbia, Japan, Lithuania, New Zealand, Norway, Sweden, USA

11,541 adults age 18 to 65, living in towns with populations >30,000 in Hong Kong

Survey, interview Main type of housing in neighborhood as a

measure of residential density; access to shops; presence of transit stops; presence of sidewalks, bicycle facilities, free or low cost recreation facilities; crime; neighborhood activity-friendliness

Shan (2014) China

595 park visitors age 15 and older in Guangzhou

Distance from urban green space

Shi et al. (2006) China

824 Students from 16 Assignment of schools to

classes in grades 7 and 8, urban/rural by authors in 8 schools in Xuzhou and Zhenjiang prefectures

Urban vs. rural school

Physical activity type/physical activity

Covariates3 Results

Community Transportation and Demos

recreation, work/survey or interview

Neighborhood Transportation/survey or Demos interview

Transportation/survey or None interview

Neighborhood General (not

specified )/IPAQ or modified IPAQ.

Distance from Transportation/survey or Demos residence interview

Community Transportation and Demos

recreation, work/survey or interview

safety associated with decreased likelihood of active travel.

(1) Availability of educational institutions, improved sanitation and housing infrastructure, access to markets associated with declines in occupational and total physical activity. (2) Health facilities associated with declines in occupational activity. (3) 10 community level urbanization dimensions associated with significant declines in occupational activity over time, especially for men.

(1) Traditional neighborhood associated with shortest average distance of walking bicycling trips, compared to planned neighborhood; private sector neighborhood has highest average distance of walking, bicycling trips.

(2) Traditional neighborhood has highest non-motorized travel. (3) For nonwork trips, residents in traditional neighborhood have most frequent non-motorized travel.

(4) Greater trip distance associated with decrease in non-motorized travel.

(5) Neighborhood type not associated with transit vs. non-motorized travel for travel to work. (6) One planned community associated with greater likelihood of non-motorized travel versus driving.

(1) Shorter distance associated with increased likelihood of active travel.

(2) Increased distance to rail station associated with decreased probability of walking, bicycling to transit station. (3) Living closer to rail station associated with increased probability of walking to station.

(4) Increased distance to bus stop associated with increased probability of walking, bicycling to transit station. (5) No bicycle parking facility at transit station associated with not bicycling to transit station. (1) Many shops nearby, transit stop in neighborhood, sidewalks on most streets, bicycle facilities, and low-cost recreational facilities associated with physical activity prevalence. (2) Number of physical activity-supportive built-environment attributes associated with meeting guidelines for physical activity.

Respondents who must walk more than 20 min to urban green space are less likely to walk to urban green space, compared to residents within 10 min walking distance. (1) Urban vs. rural boys have no significant difference in vigorous physical activity, mode of commuting, level of house work, or total physical activity. (2) Urban vs. rural girls have no significant difference in vigorous physical activity. (3) Rural girls participated in significantly more housework and more total

Su et al. (2014) China

1434 residents of 30 neighborhoods in 3 types of administrative planning units in Hangzhou

Observation/ environmental audit, survey

Perceived residential density, access to commercial and physical activity destinations, access to public services, street connectivity, sidewalk and bike lane quality, aesthetic quality, safety from traffic and crime.

Van de Poel China et al. (2009)

Xu et al. (2009) China

6484 adults from 189 communities in 1991; 6197 adults from 192 communities in 2004 2375 students age 13-15 in 24 junior high schools in 10 urban districts in Nanjing

Survey

GIS, measure of public green space in district

Measure of urbanicity, including land use, transportation infrastructure, services, and socioeconomic context

Residential density, public green space

Xu et al. (2010) China

Yang et al. (2010)

2660 students age 13-15 in 24 junior high schools in 10 urban districts in Nanjing

4092 commuters in Nanjing

Survey

Residential density

Trip distance, perceived safety of bicycling

Yang (2010) China

Yang et al. (2012)

Members of 25 households in each of 48 urban neighborhoods in Beijing

1499 workers in 48 neighborhoods in Beijing

Division of city into three areas by age, by authors

Distance to city's geometric center, distance to the closest job center, distance to the closest subway station

Central core, suburban zone, and hybrid area between core and suburbs (defined by age)

Zacharias (2007)

Zhang et al. (2011)

1326 pedestrians 141 observed itineraries in Tianjin central area 1100 residents age 40-80 in 13 communities in three districts in Shanghai

Survey,

observation/environmental

Survey

Retail location

Environmental design, environmental greenness and sanitation, residential environment, land-use accessibility, traffic environment, environment safety

Zhang et al. (2014a)

1572 older residents (age GIS 60 + ) of 102 rural neighborhoods in Zhongshan Metropolitan

Density, bike lane density, distance to transit, distance to the central business district (destination accessibility), and land use diversity

Zhang et al. (2014b)

4308 older residents (age GIS 60 4- ) in Zhongshan Metropolitan area

Population density, sidewalk density, percentage of green space land use, bus-stop density, commercial accessibility, and land use diversity

Neighborhood Recreation/IPAQ Demos

Community General (not Demos,

specified )/survey or other interview

Urban district Recreation/IPAQ or Demos,

modified IPAQ other

Community Recreation/IPAQ or Demos

modified IPAQ

Individual Transportation/survey or Demos respondent interview

Neighborhood Transportation/survey or Demos interview

Area of city Transportation/survey or Demos interview

Individual Transportation/survey or None interview, tracking study

Individual General (not Demos,

specified )/pedometer other

Neighborhood General (not Demos,

specified )/survey or other interview

Neighborhood General (not Demos,

specified )/survey or other interview

physical activity, compared to urban girls.

(1) Men with higher perceived access to physical activity destinations have higher levels of leisure time physical activity.

(2) Women with higher perceived aesthetic quality had more leisure time walking.

(3) Neighborhood density inversely associated with leisure time walking in women.

Rural residence associated with participation in heavy or very heavy physical activity as part of daily activities.

(1) Living in higher density residential areas associated with less time on physical activity.

(2) Residents in higher and middle residential tertile had lower odds of being in higher physical activity category. (3) For boys, residential density negatively associated with physical activity.

Students in higher residential density tertile spent less time on physical activity

(1 ) Trip distance associated with likelihood of commuting by bicycle. (2) Perceived safety not significantly associated with tendency to commute by bicycle.

Living closer to urban rail stations associated with increased travel by rail and decreased travel by bicycle.

Suburban areas have higher non-motorized travel for commuting, compared to central core and hybrid areas. Pedestrian generators and large shopping centers at ends of pedestrian shopping street associated with longer walking trips. Body building club, traffic safety, street design, ground surface, crossing the street, and activity environment (safety from pets) were PE factors with greatest impact on physical activity.

(1) living in most-populated (rural) environment, high land use mixture, and dense bike lanes associated with more and longer cycling trips. (2) Convenient bus service and greater distance to central business district associated with fewer cycling trips. (1) Population density, sidewalk density, increased green space, and bus stop density associated with decreased probability of having zero walking trips. (2) Neighborhoods with dense sidewalks, abundant and easily accessible commercial establishments in walking distance, high percentage of green space, and dense bus stops, associated with increased frequency of walking trips. (3) High density and high land use mixture associated with lower frequency of walking trips. (4) Sidewalk density, percentage of green space, dense bus stops, and more commercial destinations, associated with increased duration of walking.

Reference Country1 Sample Environmental factors, data source2 Environmental factors examined Analyzed geographic unit Physical activity type/physical activity measure Covariates3 Results

Zhao and Lu China 370 employed residents Census, GIS Density, mixed land use, transport Urban Transportation/survey or Demos, (1) In higher density and higher jobs-housing

(2011) living on the urban fringe in Beijing accessibility, local jobs-housing balance, transport access subdistrict interview other balance areas, probability of choosing walking, cycling or another mode of transit is higher than choosing public transit. (2) In areas with high density and high jobs-housing balance, probability of choosing walking, cycling or another mode of transit is higher than probability of commuting by car.

Zhao (2013) China 712 employed residents Census Net density of residents and employment, Residential Transportation/survey or Demos (1) Jobs-housing balance and higher

in 60 communities in local jobs-housing balance, density of main subdistrict interview residential density associated with increased

central and inner and secondary roads, transit access, distance likelihood of commuting by non-motorized

suburban areas of Beijing to city center transport. (2) Higher job density associated with decreased likelihood of commuting by non-motorized transport. (3) Higher density of main roads and increase in distance to city center associated with increase in motorized transport, compared to non-motorized transport. (4) Higher density of secondary roads associated with increase in non-motorized transport. (5) Higher transit access associated with increase in public transport use, compared to non-motorized transport.

Zhao and Deng China 1544 riders at 16 Rapid GIS Station type (elevated or underground, 800 m buffer Transportation/survey or Demos (1) Terminal station associated with walking

(2013) Rail Transit stations in Nanjing station function); station density gradient; distance to city center; length of side streets; number of feeder bus lines surrounding rail stations interview longer distances, transfer station associated with walking shorter distances, compared to typical station. (2) Elevated station associated with walking longer distances, compared to an underground station. (3) Underground station associated with walking longer distances, compared to bus rapid transit station.

Zhao (2014) China 613 employed heads of households in Beijing GIS, survey Population density, employment density, jobs-housing balance, distance to old city center, land use diversity, local street density, number of street crossings (connectivity), density of main roads and expressways, crossings of main road and expressways, exclusive bike lanes, proximity to transit. Community Transportation/survey or interview Demos (1) Jobs-housing balance, destination accessibility, employment density, number of local street crossings, land use diversity, and exclusive bike lanes associated with commuting by bicycle (compared to motorized mode). (2) Population density has no significant effect on commuting by bicycle. (3) Higher levels of public transit service and larger numbers of main-road crossings associated with reductions in commuting by bicycle.

Zhou et al. China 478 parents of students at Survey Residential density, land use diversity, facility Neighborhood Transportation and Demos (1) Living in downtown area more positively

(2013) 2 urban and suburban Shanghai junior high schools (completed questionnaires), 235 also provided accelerometer data access, street connectivity, walking and cycling facilities, aesthetics, pedestrian safety, crime safety recreation/IPAQ or modified IPAQ, accelerometer associated with transportation and leisure time physical activity, compared to living in suburbs. (2) Residential density and poorer street connectivity associated with higher levels of leisure-time physical activity.

1 For studies that included China and other countries, only results for China are reported where it was possible to distinguish such results. Studies that include results for other countries (in addition to China) are noted. (See Table 2).

2 "Survey" or "interview" indicates that respondents provided information about their neighborhoods or local environments. "Observation/environmental audit" denotes that built environment data were collected through observation by the researchers.

3 "Demos" refers to demographic covariates of individual respondents (e.g., age, income, gender) and household characteristics (e.g., car ownership, household income). Other covariates are labeled "other." Other covariates include attitudes (e.g., towards walking, driving); lifestyle factors (e.g., alcohol or tobacco use); health status (e.g., BMI); and other factors.

1 1 1 1 1 1

Health Urban Transportation Social science- Other Sports and

planning other exercise

Fig. 1. The number of studies that contain one or more authors from various disciplines. Many studies include multiple authors and represent more than one discipline.

noting that the present study also finds support for the association between physical activity for transportation and land use mix (proximal non-residential locations) in Chinese cities.

As these studies demonstrate, the built environment of Chinese cities and physical activity are clearly associated. Evidence for this association should increase as the number of studies grows over time. This review is limited by its exclusion of studies published in languages other than English. Research published in Chinese, in particular, should be considered.

Additional research on active living in China is greatly needed. For improved validity, future studies should follow the trend in this field towards objective measures of the built environment, while also continuing to include explicit measures of the perceived environment. Though GIS is the standard measure of objective built environment features for much active living research in developed countries, it is unreasonable to expect widespread use of GIS in China, where detailed GIS data is not uniformly available. In the mean time, environmental audits offer one alternative to measure objective built environment features. Some environmental audits have been developed or modified for use in China, including the Irvine Minnesota Inventory—China (Alfonzo et al., 2014), Environment in Asia Scan Tool (Cerin et al., 2013a, 2013b); and the China Urban Built Environment Scan Tool (Su et al., 2014).

Most existing active living research in China is correlational (as in Saelens and Handy, 2008). There is a need for longitudinal and quasi-experimental studies to establish stronger causal relationships between features of the built environment and physical activity outcomes. Research is also needed on smaller Chinese cities that are less well represented in existing research. Indeed, Tier Two and Tier Three cities in China are among the most rapidly developing (Craig and Qiang, 2010). Their built environments and population characteristics may vary from those of megacities such as Hong Kong and Beijing that are the focus of much existing research.

As in Saelens and Handy (2008), many questions remain about associations between specific built environment features and specific forms of physical activity. Needed are future studies that test explicit conceptual frameworks. Sixteen of the 42 studies reviewed in this paper measured physical activity in a general way. Needed is more consistency in defining physical activity as tied to transportation, recreation, or work, to better understand its potential relationship with the built environment.

Going forward, active living research should be framed within a specific Chinese context in terms of conceptual models, variables, and interpretation of findings. Take, for example, the issue of urban residence, which is associated with lower rates of physical activity in China (Bauman et al., 2011; Bosdriesz et al., 2012; Monda et al., 2007; Ng et al., 2009; Shi et al., 2006; Van de Poel et al., 2009). In developed countries, urban residence is routinely linked to higher rates of physical activity, and especially active travel (Saelens and Handy, 2008). In

research in developed countries, urban residence is typically compared to suburban residence. Research in China, however, often contrasts urban with rural rather than suburban residence. Urban residence in China is frequently associated with higher rates of affluence, greater access to automobiles and more sedentary occupations (Day et al., 2013), compared to rural residence. Rural residents in China frequently walk or bicycle for travel, unlike many rural and suburban residents in developed countries. Thus, findings on the link between urban residence and physical activity must be interpreted carefully.

Also, it is important to know more about the specific characteristics of urban residents in China, to understand their physical activity patterns. China has seen enormous growth in the number of residents who have moved from rural to urban areas in recent years. Place of origin (urban versus rural) may affect urban residents' behavior and their attitudes towards some built environment features (e.g., density, traffic safety). Future research should include information about respondents' urban or rural registration status (or hukou) to help make sense of these behaviors and attitudes.

In many Chinese cities, the wide availability of public transportation means that individuals frequently have choices among active travel modes (bus, subway, bicycling, walking), and not only between active and motorized travel. Researchers maybe interested in shifts within active travel modes (which have different physical activity implications) as well as shifts between active and motorized travel. Also note that not all bicycling in China is active. The huge popularity of electronic or e-bikes in China (Ramzy, 2009) means that many residents who bicycle for travel or recreation, do not necessarily engage in physical activity. Future research should be sensitive to this distinction.

Air pollution was included as a built environment factor in only two studies in this review (Cerin et al., 2013a; Zhang et al., 2011). Yet air pollution is a huge concern among Chinese citizens and a growing priority among policy makers (c.f., Secretariat for Clean Air Alliance of China, 2013). Future research should include air pollution as both independent and dependent variables, since high air pollution levels may reduce outdoor activity and reduced active travel may increase air pollution (through increased motorized travel).

Density is another issue that may have distinct consequences for physical activity in China and other developing countries. In research in developed countries, density is commonly associated with increased physical activity (Saelens and Handy, 2008), typically reflecting the availability of active travel modes in dense urban areas. In this paper, however, density is linked to physical activity in some studies (Alfonzo et al., 2014; Cerin et al., 2012a; Feng et al., 2014; Pan et al., 2009; Zhao and Lu, 2011; Zhao and Deng, 2013) but not in others (Jiang et al., 2012; Pan et al., 2009; Zhao and Deng, 2013; Zhao, 2014; Zhou et al., 2013). Also, some studies find a negative association between density and physical activity for recreation (Su et al., 2014; Xu et al., 2009,2010). It may be that the very high density levels in Chinese megacities discourage recreational physical activity by limiting per capita park space and causing perceived overcrowding. This relationship needs further examination.

Future active living research should also examine the impact of traffic safety (Cars in China: Dream machines, 2005). China is a nation of many new drivers (Hessler, 2007) and traffic accidents are common. Concerns about traffic safety may impact walking and bicycling, especially for children. In this review, findings on the association between traffic safety and physical activity were mixed (Alfonzo et al., 2014; Cerin et al., 2012a, 2012b; Cerin et al., 2013a, 2013b, Cerin et al., 2014; Jiang et al., 2012; Li et al., 2014; Naess, 2013; Su et al., 2014; Yang et al., 2010; Zhang et al., 2011; Zhou et al., 2013). More research is needed to understand the association between perceived traffic safety and physical activity.

Several studies examined associations between fear of crime and physical activity (Adams et al., 2013; Alfonzo et al., 2014; Cerin et al., 2012a, 2012b; Cerin et al., 2013a, 2013b, 2014; Ding et al., 2013; Jiang et al., 2012; Li et al., 2006, 2014; Sallis et al., 2009; Su et al., 2014;

Characterization of studies by how environmental factors were measured, the environmental scale of the study, the type(s) of physical activity measured, and which results were expected, unexpected, and/or null.

Article How environmental Environmental scale Physical activity type Expected Unexpected Null

factor measured

Objective Perceived Micro Meso Macro Transport Recreation Work General

(O) (P) (Mi) (Me) (Ma) (T) (R) (W) (G)

Adams et al. (2013) X X X X PMeG2+6+7+10+12a PMeG7+10b PMeG2b

Aldingeret al. (2008) X X X OMiG9+10+11

Alfonzo et al. (2014) X X X X X OMeT3+4+5+6+7+s+9+i°+i2- PMeG11; PMeR11

OMeR3 + 4+5 + 6+7 + s + 9+10 + 12

An and Zheng (2014) X X X PMiR2-10

Bauman etal. (2011) X X X X OMaW1; OMaT1 OMaR1

Bosdriesz etal. (2012) X X X X OMaG1,11,15b

Cerin etal. (2012a) X X X PMeT2-3-4-6-8-11-12; PMeG2-6-11 PMeT4-7-10; PMeG4-7-10

Cerin etal. (2012b) X X X PMeR3-4-6-10 PMeR3-4-7-8-9-11

Cerin et al. (2013a) X X 2 X OMeR5-7-8-9-10-11-16 OMeR10

Cerin etal. (2013b) X X X X OMeT3-7-10-14 OMeG7; OMeT7 OMeT4-6-8; OMeG4-6-8

Cerin et al. (2014) X X X PMeG3-9b; PMeG3+4+7+8+9+12b

Ding etal. (2013) X X X PMeG2-6-10-13 PMeG7

Feng et al. (2014) X X X X OMeT11-12; OMeR2-11 OMeT2; OMeR2-12

Jiang et al. (2012) X X X OMeT7+8+9 OMeT2-11-12

Li et al. (2006) X X X X X OMeG3-5-6-10; PMeG7 OMeG10,11

Li et al. (2014) X X X PMeR2,3,4,7,8,9

Mondaet al. (2007) X X X OMaW1

Naess (2009) X X X OMeT2

Naess (2010) X X X OMeT2 OMeT2

Naess(2013) X X X X X PMeT2; PMaT11-15 PMeT8

Ng et al. (2009) X X X X X OMaWG1 ; OMaWG1+3+11+12 OMaW3 OMaG11,12

Pan et al. (2009) X X X OMeT2+3+4+11+12 OMeT2+3+4+11+12

Panet al. (2010) X X X OMeT2-13 OMeT3

Sallis et al. (2009) X X X PMeG2-6-10-13b; PMeG2 + 6+7+10 + 11 + 12b PMeG7-12b

Shan(2014) X X X OMeT2

Shi et al. (2006) X X X X X OMaG1; OMaW1 OMaR1; OMaW1; OMaG1

Su et al. (2014) X X X PMeR9,10 PMeR12 PMeR2-4-6-7-8-13;

PMeR2 + 6 + 7 + 8 + 9 + 10 + 11

Van de Poel et al. (2009) X X X OMaG1

Xu et al. (2009) X X X OMaR12

Xu et al. (2010) X X X OMaR12

Yang(2010) X X X OMeT2 OMeT2

Yang et al. (2010) X X X OMeT2 OMeT8

Yang et al. (2012) X X X OMaT11

Zacharias (2007) X X X OMeT2

Zhang etal. (2011) X X X PMeG6,8,10,14 PMeG2,4,5,7,8,11,12,16

Zhang et al. (2014a) X X X OMeG2-3-11-12-13

Zhang et al. (2014b) X X X OMeG2-3-5-6-12 OMeG3,12

Zhao and Lu (2011) X X X OMeT3,12 OMeT3

Zhao(2013) X X X OMaT2-3-4-12 OMaT12

Zhao and Deng (2013) X X X OMeT11 OMeT2,4

Zhao(2014) X X X OMeT3,4,13 OMeT3,4 OMeT12

Zhou et al. (2013) X X X X PMeT11; PMeR11-12 PMeR4 PMeT3-4-6-9-7-8-10-12-13

a Findings of composite characterization of built environment are indicated by +. b Findings pertain to multiple countries, including China.

Results in the expected or unexpected/null direction, organized by environmental factors and by type of physical activity. Each study may have multiple results.

Types of physical activity

Transportation Recreation Work General

Expected Unexpected or null Expected Unexpected or null Expected Unexpected or null Expected Unexpected or null

1 Urban (vs. rural) 1 0 1 2 4 1 4 1

2 Distance to specific non-residential land uses 9 7 1 3 0 0 2 1

3 Proximal non-residential destinations 9 5 4 2 0 1 8 2

4 Network characteristics 5 7 2 4 0 0 1 3

5 Parks and open space 1 0 2 0 0 0 2 1

6 Pedestrian infrastructure 3 2 2 1 0 0 7 1

7 Crime 3 3 2 3 0 0 4 6

8 Traffic safety 3 4 2 3 0 0 2 2

9 Aesthetics 2 1 3 3 0 0 2 0

10 Non park physical activity facilities 2 2 4 2 0 0 6 3

11 Other 4 3 2 2 0 0 6 4

12 Density 6 5 2 4 0 0 6 4

13 Bicycling facilities 2 1 0 1 0 0 3 1

14 Stray animals 1 0 0 0 0 0 1 0

15 Weather 1 0 0 0 0 0 1 0

16 Pollution 0 0 1 0 0 0 0 1

Composite 3 1 1 1 1 0 5 1

"Composite" indicates cases where environmental factors were combined to examine their association with physical activity.

Zhang et al., 2011; Zhou et al., 2013), with mixed findings. Crime rates have increased significantly in China during the market reforms of the last three decades (Nielson and Smyth, 2005.) Researchers should consider unique factors tied to perceived danger and safety for Chinese residents. Consider, for example, the concept of guanxi, the network of personal bonds that shapes all aspects of life in China and which has been linked to perceived safety (Zhang et al., 2009). Guanxi may mediate the relationship between the built environment, fear of crime, and physical activity at the neighborhood level.

Few studies in this review included children, yet growing childhood obesity is a significant concern in China (Gui et al., 2010; Markey, 2006). Boys especially are at risk, due to their special status in Chinese society. Parent and grandparents are tempted to spoil boys with food. Youth are the focus ofmuch active living research in the United States and in other developed countries because of the long-term impacts of low physical activity among young people. More research is needed on the association between built environments and physical activity among youth in China.

Several studies examined composite features of the entire neighborhoods that are associated with physical activity (Adams et al., 2013; Aldinger et al., 2008; Alfonzo et al., 2014; Cerin et al., 2014; Jiang et al., 2012; Ng et al., 2009; Pan et al., 2009; Sallis et al., 2009; Su et al., 2014). Many studies compared walkable versus nonwalkable neighborhoods; results were most often in the expected direction. Future research should consider the associations with physical activity of popular development types in Chinese cities (e.g., suburban new towns).

Urban planning scholars, policy makers, and practitioners have identified alternate models for urban development in China, that challenge prevailing auto-centric patterns (c.f., Energy Innovation Institute, 2011; Han et al., 2014; Harvey and Busch, 2012; Urban Land Institute, 2013). Recommendations are familiar: greater transit reliance, smaller blocks and lively street fronts to encourage walking, dense networks of streets and paths, and others. Findings from active living research can provide valuable empirical evidence to support efforts to maximize health and environmental benefits in future planning and development in Chinese cities.

Conflict of interest

The author declares that there are no conflicts of interest.

Transparency Document

The Transparency Document associated with this article can be found, in online version.

Acknowledgments

Sincere thanks to Xinyi Liu, who assisted with identifying studies for this review. Thanks also to Brien Saelens and Susan Handy, whose paper served as a model for this review.

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