Introduction

As urbanization continues, public health issues are becoming more prominent, and in 2013 the World Health Organization (WHO) ranked physical inactivity as the fourth leading risk factor for death, noting that physical activity in China has declined by 45% over the past 18 years. At the same time, several health studies in the public health field have confirmed that walking activity can lead to many positive health outcomes, such as reducing the incidence of many chronic diseases, preventing obesity, and reducing anxiety and stress. As a result, various international health organizations have called for improving human health by optimizing urban walking environments and promoting walking activities. As early as the 1960s, scholars such as Lewis Mumford, Jane Jacobs, and William H. Whyte began to question the dominance of the automobile and advocate pedestrian-friendly urban design with a human focus. However, automobile-oriented road planning and people's over-dependence on automobiles have resulted in a pedestrian environment that has always been neglected.

The fields of public health, urban planning, and transportation planning use walkability to describe the built environment's facilitation of walking activities. Indeed, the benefits of walking for travel also include reduced traffic congestion, air pollution, improved public health environments, enhanced positive community relations, and the promotion of public transportation and enhanced parcel values. Thus, as a mode of travel, walking has the potential to simultaneously contribute to sustainable urban development in terms of health, economic, social, and environmental aspects1.

Research work on walkability has been carried out earlier in various fields at home and abroad, and in the past two decades, there has been a trend of a large increase in the number of studies and an update of research content in terms of theoretical foundations, research methods, research content, and the application of big data. Therefore, with the help of scientometric and network analysis methods, we can objectively and comprehensively reveal the overall publication and research dynamics of walking appropriateness, which can actively promote the development of research work in related fields in China.

Data sources and research methods

In this paper, the Web of Science (WoS) core collection of Science Citation Index extended (SCIE) and Social Sciences Citation Index (SSCI) citation index databases were used as source databases for searching. In order to have a more comprehensive understanding of the research trends in this field, the search terms of this study are The "Topic" field also includes "walk suitability" and "walking environment". The "Topic" field was searched for topics, including articles with the above keywords in the titles, keywords and abstracts of articles in the WOS database and core journal databases in the field. The time span of the search was "1997–2019", and the types of articles were selected to represent most of the relatively complete literature of journal articles. The search yielded 1283 eligible articles, with data saved as of July 10, 2019. BibExcel, a scientometric and knowledge network analysis tool, VOSview, a visualization software, and Histcite literature analysis software were used to perform the econometric analysis and knowledge network analysis of the literature.

Issue overview

Analysis of the number of articles published

The change in the number of academic papers in a certain research direction is an important indicator for analyzing the development trend of that research topic. At the same time, this indicator reflects the changes in the level of knowledge in the discipline. Statistical analysis of the annual number of articles on walkability can clarify the current status of research and future trends in the field. This study summarizes the trends in the number of research papers on urban vitality from 1997 to 2018 (Fig. 1).

Figure 1
figure 1

Overview of the number of articles published annually.

Full size image

According to the annual article volume statistics, research on walking suitability has received increasing attention from scholars. Prior to 2004, less than 10 articles were published annually in this area of research, and since 2004, the field has been gaining attention from researchers, especially between 2014 and 2016, with a rapid increase to 191 articles per year as of 2018, and this number continues to grow. Compared with 2016, the number of articles published doubled in 2017. In addition, the number of articles published from 2019 to 2023 is almost the same as that from 1997 to 2018. This trend suggests that the field of walkability will receive more attention from researchers worldwide. The significant increase in the number of annual articles in this field in recent years may be due to the urbanization process, which has led to many urban issues such as health crisis and traffic congestion.

Country of issue analysis

When the countries of publication were analyzed, all research papers on walking suitability came from 65 countries or regions in the world. Figure 2 shows the top 20 countries or regions with a total of 1677 papers, accounting for 87% of the total papers published, mainly in Europe, the Americas, Asia, and Oceania. Among them, the United States is the most active country in the study of walkability, with 542 articles, accounting for 28% of the total number of articles published, which is more than twice the number of articles published in the second place, Australia. In addition, four Asian countries, China, Japan, Korea, and Malaysia, were among the top 20 countries in this field, and China was ranked fourth in the world with 125 articles, accounting for 6.5% of the total number of articles published. It can be seen that Chinese researchers have contributed significantly to the development of walkability research worldwide.

Figure 2
figure 2

Ranking of the total number of articles issued by the country.

Full size image

Keyword frequency analysis

Studying the evolutionary dynamics of keywords can provide a quick understanding of the research trends and hot spots in the field. The study counted the key words in the field of walking suitability research in WOS from 1997 to 2019 and kept the key words with a word frequency greater than 5 per year (Fig. 3), and found that no high-frequency words appeared in the articles published before 2008, and the research content was scattered without obvious research hotspots. From 2008 onward, some key words began to appear consistently and at high frequencies in the research literature on walking suitability, e.g., physical activity has consistently been an important research content in this field since 2008. Since 2010, the number of research perspectives on walkability has been increasing, and research on the relationship between built environment, walking, obesity, elderly, community environment, urban design, and social environment and walkability has become a research hotspot in the field and has received continuous attention from researchers. In addition, the number of research papers in the direction of travel patterns, virtual reality, and big data is also on the upswing.

Figure 3
figure 3

Frequency of keyword occurrence.

Full size image

Analysis of important journals

A total of 2500 articles within the search were published in 402 different publications. Among them, 199 publications have published only 1 paper in the field, and 21 journals have published more than 10 articles in all, and these journals have published a total of 1003 articles, that's more than half of the total number of articles published. This study counted the 10 most active journals among these 21 important journals (Table 1), mainly in the disciplines of public health, transportation, medicine, sports, urban planning, landscape, and sociology2. These journals not only have the highest contribution of publications, but also, 7 journals have the top 10 total citations of their articles, which shows that these journals are important journals in the field in terms of publication volume and academic influence.

Table 1 Top 10 journals by volume of published articles.
Full size table

At the same time, comparing the total number of citations and the average number of citations of each journal, "International Journal of Behavioral Nutrition and Physical Activity" and "American Journal of Preventive Medicine" are the top two journals in terms of total number of citations and average number of citations. Two, the articles in this field of "American Journal of Preventive Medicine" are far more cited than those of other journals in terms of total citations or both.

Knowledge base

The number of articles published in each discipline was analyzed, and the top ten disciplines were mainly concentrated in the fields of public health, environmental science, transportation, and urban planning. Histcite software was used to build a database of hot literature to further analyze the most influential articles in the field of walkability, as shown in Fig. 4. The top 30 database documents with LCS scores were selected, and the 16 classic documents with more than 100 citations were analyzed. Among them, six articles focused on the potential association between built environment and walking type and physical health; four articles explored the intrinsic association between urban form, transportation, and walkability; four articles explored the related content of walkability evaluation; the remaining two articles studied the relationship between community walkability and social attributes。

Figure 4
figure 4

Top 30 papers in LCS and their citation relationships.

Full size image

Research directions and hot spots

Keywords can express the research theme of the article, which contains the most condensed content information of the article, and network analysis of keywords can clarify the network structure and relationship strength among research directions. The keywords in the literature were extracted and analyzed by bibexcel software, and 2039 keywords without duplication were retained after data cleaning. The keywords with word frequency greater than or equal to 20 in the literature were listed and counted (Table 2), and the popular directions in the field could be found. Subsequently, the keywords with word frequency greater than or equal to 5 were network analyzed to study the intrinsic structure and association among the research directions of walk suitability. The screening results showed that a total of 121 keywords met the conditions, and then, the above keywords were expressed visually using Vosviewer software, as shown in Fig. 5, where the nodes represent keywords, and the larger the nodes indicate the higher frequency of occurrence. The thicker the line, the more frequent the co-occurrence, the higher the correlation between the keywords, and the weaker the connection strength of some keywords, which may become a new research direction in the future. Different colors represent different clusters, as shown in the figure, it can be clearly seen that the research direction of walking suitability can be divided into 6 clusters. Among them, cluster 1 is walking suitability and planning design; cluster 2 is environment type and behavior; cluster 3 is walking suitability evaluation tools; cluster 4 is the effect of physical activity on chronic diseases; cluster 5 is physical activity of different groups; and cluster 6 is walking suitability evaluation index. Some keywords with significant correlations exist in some clusters, so the six clusters are further divided into three major research directions: walking suitability and physical activity, walking suitability evaluation, and walking suitability and planning design. Finally, each research direction is associated with different regions, and the existing research directions in each region are summarized, as well as further research directions in the future (Tables 3, 4).

Table 2 Walkability keyword statistics.
Full size table
Figure 5
figure 5

Keywords network analysis.

Full size image
Table 3 Current research directions in each region.
Full size table
Table 4 Future research directions in each region.
Full size table

Walk suitability and physical activity

The 2010 Toronto Charter for Physical Activity: A Global Call to Action defines the important role of physical activity in this field of study. Physical activity has multiple benefits including promoting well-being, maintaining physical and mental health, and preventing disease. Walking is a highly recommended form of physical activity as a low-impact, age-appropriate and environmentally friendly transportation choice.

Physical activity for different groups

Physical activity is considered to be an important intervention indicator of health level and is significantly correlated with walkability3. Since 2005, a large number of studies have been conducted on the physical activity patterns and environments of different populations, mainly involving children, adolescents, adults, older adults, women, and low-income groups. In children and adolescents, for example, research on physical activity and walking suitability has focused on safe walking, obesity, and school attendance. Traffic safety is an important influence on walking suitability and an important determinant of physical activity and walking to school in children and adolescents, and there is a significant correlation between perceived traffic safety and walking activity, and this association is stronger in girls than in boys4. And reducing traffic volume and traffic speed and increasing children's recreational areas have been shown to be important measures to increase walking safety for children and adolescents5. In terms of obesity prevention: physical activity can improve children's health including obesity6 and cardiorespiratory health7. Therefore, promoting physical activity in children to prevent obesity has become a public health priority8. Active schooling is also an important part of physical activity for children and adolescents, as well as an important means of curbing childhood obesity9.Yu C Y et al. found that parental tooness was a major factor in the choice of schooling, and that among the factors influencing parents to allow children and adolescents to walk to school, in addition to the amount of cars, a good environment, and walking distance, different dimensions such as safety, positive peer influence, and age of combined issues are also important influencing factors10. Loh et al. found that off-campus MVPA has a significant positive correlation with leisure facilities (within 2 km), walkability (1–2 km), and residential density (1 km)11. Ayse Ozbil et al. found that the spatial structure of the street network around the home is a decisive factor affecting children's motivation to go to school12.

Type of environment and behavior

Physical activity can be accumulated in a variety of ways, such as sports, recreation, active commuting (e.g., walking or cycling), and in different environments (e.g., schools, streets, parks, neighborhoods, etc.)13,14,24. Beulens et al., using big data samples from geographically linked electronic health records, analyzed the relationship between land use combination and intersection density in the built environment and hypertension and diabetes, and found that diabetes and hypertension were poorly controlled in African Americans. American patients are less common in more walkable neighborhoods25. Jia et al. followed 9440 kindergarten children from 1998 to 2007 and found that in the United States, the better the walkability of the residential area, the lower the children's body mass index and obesity risk 9 years later. This association was found in It's more pronounced among girls and suburban areas26. Joline W. J. Beulens et al. believe that air pollution, residential noise, and socioeconomic deprivation at the regional level are associated with increased risk of type 2 diabetes, while neighborhood walkability and green space have been associated with reduced risk of type 2 diabetes27 (Table 5).

Table 5 Finds of several studies on the built environment and health.
Full size table

Walk suitability evaluation

Walking suitability evaluation index

In the process of analyzing walkability, all urban environmental characteristics related to walking may become important indicators for assessing walkability3. Existing research results, on indicators of walkability, are divided into two main dimensions: (1) to determine evaluation indicators from urban scale overlooking density, diversity, and design standards to quantitatively describe the overall urban factors affecting walkability. For example, Lu et al., studied the linkage between pedestrian suitability and urban-scale environmental influences in Hong Kong by using population density, land use mix, and street connectivity as evaluation indicators, and found that two indicators, population density and land use mix, were not significantly correlated with any area of walking, while population density was positively correlated with traffic walking and recreational walking only in the lower density range, and in the higher The higher density range was negatively correlated with recreational walking, therefore, there may be no effect on walkability in high-density cities using the above indicators36; and analytical tools such as scoring systems, simulations, regression analysis, and integral logit models are mainly applied in the evaluation of environmental walkability37. For example: Root et al. investigated the factors of community-level aesthetic scores, applied spatial regression models, and the introduced metric of spatial autocorrelation, and verified through empirical analysis that socio-environmental, economic, and spatial structure aspects play an important role in sha** community aesthetics, providing health and planning personnel with ways in which interventions can be taken31; Gallin et al. used a point system to assess the pedestrian suitability of streets, which provides a good basis for evaluating the level of service of pedestrian facilities by rating the surveyed streets with geographic information data and field research assessments38. In addition to this, the number of articles on pedestrian suitability evaluation using a composite index is on the rise. The composite index is a summation weighting of the indicators that predict a representative environment that is conducive to walking. As the composite index of walkability has gradually entered more fields such as urban economy, transportation, and real estate, it has transcended disciplinary boundaries to form walkability indices based on different evaluation indicators with specificity. For example, D'Alessandro D et al. proposed the walkability index (T-WSI) measurement method, which uses direct observation of utility, safety, urbanity, and pleasantness, four categories of 12 weighted indicators, to form a comprehensive walkability index and identify streets and elements with low walkability index to support community walkability optimization strategies proposed39. With the advancement of geospatial technology and the availability of online maps and datasets, several research teams have developed online assessment tools. For example, the Walk Score, a walkability index website, uses publicly available data (population density, intersection density, block length, etc.) to quickly and freely calculate and score the walkability of an address to nearby amenities, addressing the time-consuming nature of common measurement studies; the Walkshed website has derived a walkability The Walkshed website has spawned a walkability surface tool that assesses the quality and diversity of unimpeded access to an address within a 1-mile radius and calculates a walkability heat map by prioritizing a set of factors by the user; in addition, such walkability tools include "Walkonomics", "WalkYourPlace", and "WalkYourPlace", "WalkYourPlace", etc.40. The development of online assessment tools offers a broader prospect for the flourishing of walking suitability-related research.

Pedestrian suitability and planning design

An important purpose of the study of walkability in urban planning is to link it to urban planning and design. Locations with higher walkability tend to have more active residents and are conducive to a healthy urban life. Walkability is often related to a variety of factors, and the results of this research have contributed to the weighing of pros and cons in the planning and design process, as well as to policy development.

Population density, land use diversity, and street connectivity are considered to be important indicators of walkability. Yi Lu et al. used the above variables to investigate the correlation between pedestrian commuting and recreational walking in Hong Kong and found significantly different results; land use diversity and street connectivity were not significantly correlated with the two types of walking trips, and population density was only positively correlated with pedestrian commuting and recreational walking were positively correlated in the higher density range, and negatively correlated with recreational walking in the higher density range

Data availability

The data used to support the findings of this study are all in the manuscript.

References

  1. Hall, C. M. & Ram, Y. Walk score® and its potential contribution to the study of active transport and walkability: A critical and systematic review. Transp. Res. Part D Transp. Environ. 61(1), 310–324 (2018).

    Article  Google Scholar 

  2. Aelens, B. E. & Handy, S. L. Built environment correlates of walking: A review. Med. Sci. Sports Exerc. 40(Suppl 7), S550–S566. https://doi.org/10.1249/MSS.0b013e31817c67a4 (2008).

    Article  Google Scholar 

  3. Rebecchi, A. et al. Walkable environments and healthy urban moves: urban context features assessment framework experienced in Milan. Sustainability 11(10), 1 (2019).

    Article  Google Scholar 

  4. Mitáš, J., Sas-Nowosielski, K., Groffik, D. & Frömel, K. The safety of the neighborhood environment and physical activity in Czech and Polish adolescents. Int. J. Environ. Res. Public 15(1), 126 (2018).

    Article  Google Scholar 

  5. Rothman, L., Buliung, R., Macarthur, C., To, T. & Howard, A. Walking and child pedestrian injury: A systematic review of built environment correlates of safe walking. Injury Prev. 20(1), 41–49 (2014).

    Article  Google Scholar 

  6. Guinhouya, B. C. Physical activity in the prevention of childhood obesity. Paediatr. Perinat. Epidemiol. 26, 438–447 (2012).

    Article  PubMed  Google Scholar 

  7. Boddy, L. M. et al. Physical activity, cardiorespiratory fitness, and clustered cardiometabolic risk in 10-to12-year-old school children: The REACH Y6 Study. Am. J. Hum. Biol. 26, 446–451 (2014).

    Article  PubMed  Google Scholar 

  8. Srinivasan, S., O’Fallon, L. R. & Dearry, A. Creating healthy communities, healthy homes healthy people: Initiating a research agenda on the built environment and public health. Am. J. Public Health. 93(9), 1446–1450 (2003).

    Article  PubMed  PubMed Central  Google Scholar 

  9. Government HM. Childhood obesity: A plan for action. HM Government: London, UK (2016).

  10. Yu, C. Y. & Zhu, X. From attitude to action: What shapes attitude toward walking to/from school and how does it influence actual behaviors. Prev. Med. 90, 72–78 (2016).

    Article  PubMed  Google Scholar 

  11. Loh, V. H. Y. et al. Built environment and physical activity among adolescents: The moderating effects of neighborhood safety and social support. Int. J. Behav. Nutr. Phys. Act. 16, 1–8 (2019).

    Article  Google Scholar 

  12. Ozbil, A., Yesiltepe, D., Argin, G. & Rybarczyk, G. Children’s active school travel: Examining the combined perceived and objective built-environment factors from space syntax. Int. J. Environ. Res. Public Health 18(1), 286 (2021).

    Article  PubMed  PubMed Central  Google Scholar 

  13. Sallis, J. F. et al. Co-benefits of designing communities for active living: An exploration of literature. Int. J. Behav. Nutr. Phys. 12, 1–10 (2015).

    Article  Google Scholar 

  14. Sallis, J. F. Measuring Physical activity environments: A brief history. Am. J. Prev. Med. 36(Suppl 4), 1 (2009).

    ADS  Google Scholar 

  15. Lu, L., Sarkar, C. & **ao, Y. The effect of street-level greenery on walking behavior: Evidence from Hong Kong. Soc. Sci. Med. 208, 41–49 (2018).

    Article  PubMed  Google Scholar 

  16. Saelens, B. E., Sallis, J. F., Black, J. B. & Chen, D. Neighborhood-based differ- ences in physical activity: An environment scale evaluation. Am. J. Public Health. 93, 1552–1558 (2003).

    Article  PubMed  PubMed Central  Google Scholar 

  17. Witten, K. et al. Neighborhood built environment and transport and leisure physical activity: findings using objective exposure and outcome measures in New Zealand. Environ. Health Perspect. 120(7), 971–977 (2012).

    Article  PubMed  PubMed Central  Google Scholar 

  18. Noonan, R. J., Boddy, L. M., Knowles, Z. R. & Fairclough, S. J. Fitness, fatness and active school commuting among Liverpool schoolchildren. Int. J. Environ. Res. Public Health 14(9), 995 (2017).

    Article  PubMed  PubMed Central  Google Scholar 

  19. Yu, J. et al. The associations of built environment with older people recreational walking and physical activity in a Chinese small-scale city of Yiwu. Int. J. Environ. Res. Public Health 18(5), 2699 (2021).

    Article  PubMed  PubMed Central  Google Scholar 

  20. Cerin, E. et al. Do neighbourhood traffic-related air pollution and socio-economic status moderate the associations of the neighbourhood physical environment with cognitive function? Findings from the AusDiab study. Sci. Total Environ. 858(3), 160028 (2023).

    Article  ADS  CAS  PubMed  Google Scholar 

  21. Mokdad, A. H. et al. The continuing epidemics of obesity and diabetes in the United States. JAMA 286, 1195–1200 (2001).

    Article  CAS  PubMed  Google Scholar 

  22. Sallis, J. F. et al. Neighborhood built environment and socioeconomic status in relation to physical activity, sedentary behavior, and weight status of adolescents. Prev. Med. Int. J. Devot. Pract. Theory. 110, 47–54 (2018).

    Article  Google Scholar 

  23. Reyes, C. et al. Association between over- weight and obesity and risk of clinically diagnosed knee, hip, and hand osteoarthritis: A population-based cohort study. Arthritis Rheum. 68, 1869–1875 (2016).

    Article  Google Scholar 

  24. Dendup, T., Feng, X., Clingan, S. & Astell-Burt, T. Environmental risk factors for develo** type 2 diabetes mellitus: A systematic review. Int. J. Environ. Res. Public Health 15(1), 78 (2018).

    Article  PubMed  PubMed Central  Google Scholar 

  25. Lê-Scherban, F. et al. Identifying neighborhood characteristics associated with diabetes and hypertension control in an urban African-American population using geo-linked electronic health records. Prev. Med. Rep. 15, 100953 (2019).

    Article  PubMed  PubMed Central  Google Scholar 

  26. Jia, P., Xue, H., Cheng, X., Wang, Y. G. & Wang, Y. F. Association of neighborhood built environments with childhood obesity: Evidence from a 9-year longitudinal, nationally representative survey in the US. Environ. Int. 128, 158–164 (2019).

    Article  PubMed  Google Scholar 

  27. Beulens, J. W. J. et al. Environmental risk factors of type 2 diabetes—An exposome approach. Diabetologia 65(2), 263–274 (2022).

    Article  CAS  PubMed  Google Scholar 

  28. Lu, Y., **ao, Y. & Ye, Y. Urban density, diversity and design: Is more always better for walking? A study from Hong Kong. Prev. Med. 103, 1 (2016).

    Google Scholar 

  29. Oliver, L., Schuurman, N., Hall, A. & Hayes, M. Assessing the influence of the built environment on physical activity for utility and recreation in suburban metro Vancouver. BMC Public Health 11, 959 (2011).

    Article  PubMed  PubMed Central  Google Scholar 

  30. Van Cauwenberg, J. et al. Environmental influences on older adults’ transportation cycling experiences: A study using bike-along interviews. Landsc. Urban Plan. 169, 37–46 (2018).

    Article  Google Scholar 

  31. Root, E. D., Silbernagel, K. & Litt, J. S. Unpacking healthy landscapes: Empirical assessment of neighborhood aesthetic ratings in an urban setting. Landsc. Urban Plann. 168, 38–47 (2017).

    Article  Google Scholar 

  32. Marshall, J. D., Brauer, M. & Frank, L. D. Healthy neighborhoods: Walkability and air pollution. Environ. Health Perspect. 117(11), 1752–1759 (2009).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  33. Aghaabbasi, M., Moeinaddini, M., Shah, M. Z. & Asadi-Shekari, Z. A new assessment model to evaluate the microscale sidewalk design factors at the neighbourhood level. J. Transp. Health 5, 97–112 (2017).

    Article  Google Scholar 

  34. Aghaabbasi, M., Moeinaddini, M., Shah, M. Z., Shekari, Z. A. & Kermani, M. A. Evaluating the capability of walkability audit tools for assessing sidewalks. Sustain. Cities Soc. 37, 475–484 (2017).

    Article  Google Scholar 

  35. Su, M. et al. Objective assessment of urban built environment related to physical activity-development, reliability and validity of the China Urban Built Environment Scan Tool (CUBEST). BMC Public Health 14(1), 109–109 (2014).

    Article  PubMed  PubMed Central  Google Scholar 

  36. Cerin, E. et al. Sharing good NEWS across the world: develo** comparable scores across 12 countries for the Neighborhood Environment Walkability Scale (NEWS). BMC Public Health 13(1), 309 (2013).

    Article  PubMed  PubMed Central  Google Scholar 

  37. Bivina, G. R., Parida, P., Advani, M. & Parida, M. Pedestrian level of service model for evaluating and improving sidewalks from various land uses. Eur. Transp. 67, 1 (2018).

    Google Scholar 

  38. Gallin, N. Quantifying pedestrian friendliness–guidelines for assessing pedestrian level of service. Road Transp. Res. 10(1), 47 (2001).

    Google Scholar 

  39. D’Alessandro, D., Appolloni, L. & Capasso, L. How walkable is the city? Application of the Walking Suitability Index of the Territory (T-WSI) to the city of Rieti (Lazio Region, Central Italy). Epidemiol. Prev. 40(3–4), 237 (2016).

    PubMed  Google Scholar 

  40. Ivan, B., Cecchini, A., Congiu, T., Fancello, G. & Trunfio, G. A. Evaluating walkability: A capability-wise planning and design support system. Int. J. Geogr. Inf. Sci. 29(7–8), 1350–1374 (2015).

    Google Scholar 

  41. Lai, Y. & Kontokosta, C. E. Quantifying place: Analyzing the drivers of pedestrian activity in dense urban environments. Landsc. Urban Plan. 180, 166–178 (2018).

    Article  Google Scholar 

  42. Zuniga-Teran, A. A. et al. Neighborhood design, physical activity, and wellbeing: applying the walkability model. Int. J. Environ. Res. Public Health 14(1), 76 (2017).

    Article  PubMed  PubMed Central  Google Scholar 

  43. **, R. & Othengrafen, F. Examining the role of innovative streets in enhancing urban mobility and livability for sustainable urban transition: A review. Sustainability 15(7), 5709 (2023).

    Article  Google Scholar 

  44. Turrell, G., Haynes, M., Wilson, L. A. & Corti, B. G. Can the built environment reduce health inequalities? A study of neighbourhood socioeconomic disadvantage and walking for transport. Health Place 19, 89–98 (2013).

    Article  PubMed  Google Scholar 

  45. Foster, S. et al. Does walkable neighbourhood design influence the association between objective crime and walking. Int. J. Behav. Nutr. Phys. Act. 11(1), 100 (2014).

    Article  PubMed  PubMed Central  Google Scholar 

Download references

Funding

This study was supported Tian** Education Commission scientific research project achievements (2023SK178) Research on planning and design method of recovery of pocket parks in high-density urban areas from the perspective of urban micro-renewal.

Author information

Authors and Affiliations

  1. School of Architecture & Art Design, Hebei University of Technology, Tian**, 300401, China

    Xuan Li, Dan **e, Zhiyu Zhou, **n Zhang, Rui Li, Jiayi Li, Zeyu Chen & Jiayu Zhang

  2. Key Laboratory of Healthy Habitat Environment in Hebei Province, Tian**, 300401, China

    Xuan Li, Dan **e, Zhiyu Zhou & **n Zhang

Authors
  1. Xuan Li
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Dan **e
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Zhiyu Zhou
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. **n Zhang
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Rui Li
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. Jiayi Li
    View author publications

    You can also search for this author in PubMed Google Scholar

  7. Zeyu Chen
    View author publications

    You can also search for this author in PubMed Google Scholar

  8. Jiayu Zhang
    View author publications

    You can also search for this author in PubMed Google Scholar

Contributions

X.L.: conceptualization, investigation, writing—original draft; D.X.: conceptualization, writing—review and editing; Z.Z. and X.Z.: data curation, methodology; R.L., J.L. and Z.C.: formal analysis. J.Z.: writing—review and editing. All authors reviewed the manuscript.

Corresponding author

Correspondence to Dan **e.

Ethics declarations

Competing interests

The authors declare no competing interests.

Additional information

Publisher's note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Li, X., **e, D., Zhou, Z. et al. Visualization analysis of research progress for walkability. Sci Rep 14, 1989 (2024). https://doi.org/10.1038/s41598-024-52227-9

Download citation

  • Received:

  • Accepted:

  • Published:

  • DOI: https://doi.org/10.1038/s41598-024-52227-9

  • Springer Nature Limited