The indicators and methods used for measuring urban liveability: a scoping review.

OBJECTIVES
Liveability is a multi-dimensional and hierarchical concept which consists of various criteria and sub-criteria and may be evaluated in different ways. The aim of this study was to systematically review indicators and methods used for the evaluation of urban liveability in literature.


CONTENT
The five-stage methodological framework of Arksey and O'Malley was used to conduct this scoping review. A systematic search of electronic databases, including Scopus, Medline (via PubMed), Embase, Web of Science and EBSCO was done until May 29, 2019. Web searching, searching reference lists and hand searching was also conducted to retrieve more relevant articles. Two reviewers screened the papers for eligibility based on the inclusion criteria and extracted their key data and reported them descriptively.


SUMMARY
Sixty seven (67) out of 3,599 papers met the selection criteria. This review showed five distinct domains considered to be important components of liveability. These were Economical, Environmental, Institutional, Social, and Governance (Political) domains. The most important subdomains (indices) which were frequently applied in various studies were Environmental friendliness and Sustainability, Socio-Cultural Conditions and Economic Vibrancy and Competitiveness. We also identified seven different methodologies and six ranking tools used for assessing urban liveability. Among the quantitative methods, three methods accounted for 89.6% of the articles. These methods were the Analytical hierarchy process and entropy (AHP; n=24; 50%), Factor analysis & Principle Component Analysis (FA & PCA; n=12; 25%) and Spatial Multi-criteria Decision-making Method (Spatial; n=7; 14.6%). Among the ranking tools used, three ranking tools accounted for 65.4% of the articles. These tools were the Livable City Scientific Evaluation Standards (LCSES; n=9; 34.6%), The Global Liveable Cities Index (GLCI; n=4; 15.4%) and the Economist Intelligence Unit (EIU; n=4; 15.4%).


OUTLOOK
This paper discusses and summarizes the latest indicators and methods used for determining urban liveability. The information offered in the review can help future investigators to decide which method suits their purpose and situation better and measure urban liveability more systematically than before.

Healthcare, Education and Housing, Sanitation and Transportation, Income Equality and Demographic Burden and Diversity and Community Cohesion, 5) Political Governance: Policymaking and Implementation, Government System, Transparency and Accountability, Corruption. Further details on the subset indicators of each index can be found in referenced articles.
The studies were also grouped based on the city in which the study was conducted. Figure 3 presents the distribution of indicators in the studies from the same country. Most urban liveability studies were done in China (47.7%). In all studies of urban liveability in China, Environmental Friendliness and Sustainability indicators were used; and Socio-Cultural Condition indicators were used in 93% of them. Also, 82% of Chinese studies used Economic Vibrancy and Competitiveness indicators in urban liveability. These 3 indices and their associated indicators were the most commonly used, in our included studies.

Evaluation Model of urban liveability
Ten categories of evaluation models were used in the included studies. Qualititative Delphi methods, Analytical hierarchy process (TOPSIS and entropy), cluster analysis method, Factor analysis & Principle Component Analysis, GIS and spatial modeling, Economist Intelligence Unit & Mercer city rankings, comprehensive marking or standard method, the livable level integrated index, neural networks and GLCI. The summary of these key evaluation models and techniques for determining urban liveability, are in Table 2. From the 67 articles identi ed, 19 (23.38%) used qualitative and the rest of the studies used quantitative methods to evaluation urban liveability. The qualitative methods of evaluating urban liveability were used between 2000 to 2004 [16]. Among the quantitative methods, 4 methods

Discussions
Scoping reviews are used to map or con gure a body of evidence. This scoping review about the domains, indicators and evaluation models of urban liveability can be used in designing and planning urban structures, and improving the quality of life of urban residents, by urban health planners and policy-makers. In this review, we focused more on breadth, and included studies that showed the variation of assessing methods, rather than focusing on each domain in detail.
The review suggests that there are a large number of indicators that can be used in ranking cities for liveability. The 5 domains of urban liveability are an important base for researchers wishing to add new indices and indicators to the indices already mentioned in the literature. Each of these indexes includes a list of indicators that has been mentioned in our tables.
In this review, the most common indicators used in various studies for assessing urban liveability were identi ed.
Environmental Friendliness and Sustainability, Socio-Cultural Conditions and Economic Vibrancy and Competitiveness were the most frequently applied indices. These indicators have been used at national, state, and local levels to compare the liveability of cities and regions. Tan et al (2018) set 121 indicators in 5 economic, environmental, institutional, social and governance and political indices for ranking the livability of large world cities [17]. Cheng (2019) has also established evaluation indicators from social civilization, economic development, environmental health, resources sustainability, living amenity and public safety [7]. Liao et al (2019) created their evaluation system for 20 cities in China from 4 domains including, economic development, population situation, resources and environment [18].
Liveability indicators can be useful for monitoring progress towards achieving policy reform, engaging governments in conversation with the private and community sectors, and enhancing the connection between urban planning and public health [19]. Indicators are important because they provide benchmarks against which to monitor progress towards policy reform; and to make comparisons between and within cities. More effective and consistent use of liveability indicators is required to promote healthy, liveable and sustainable cities, and can be achieved through integrated planning across and between governments, economic infrastructure, health care, environmental protection agencies, educational facilities, and cultural and welfare organizations.
Indicators may vary with geographical locations or cultural values, and this may limit the generalization of our results.
Indicators of liveability may measure progress towards achieving a wide range of health policy outcomes, including enhanced health and reduced inequalities. Although many indicators for urban liveability were identi ed in this review, the majority require further development, before they can be operationalized and link to health datasets. In order to validate liveability indicators, consideration should also be given to testing the association between these indicators and health. This can be achieved by linking indicators measured at an appropriate scale to existing health datasets.
There is also a need to create liveability indices that are robust and related to urban planning policies [6].
Different experts or organizations have proceeded from different perspectives and used different evaluation systems for assessing urban livability. In the present review, ten different methodologies were used for evaluating urban livability. More than half of the articles had used one of the four evaluation models which were the AHP and entropy, FA and PCA, GIS and spatial model, EIU and Mercer Model.
In this scoping review, 22 studies used the AHP method (TOPSIS and entropy) for evaluating liveability. AHP is a multicriteria decision-making method which has been extensively utilized in a wide variety of areas. In this method, both quantitative and qualitative criteria can be transformed into numerical scales, and this facilitates the users' understanding about the factors chosen for evaluation, as well as their relative importance in relation to one another [1]. AHP can assist the decision maker in effectively summarizing and assessing all information, defining the right questions and determining the optimum and most appropriate solutions. This method is applied to estimate the weights of parameters, because it has a simple hierarchical structure, sound mathematical basis, widespread usage, and ability to measure inconsistencies in judgements. In the process of AHP, pair-wise comparison matrices of each factor and sub-factors are implemented through consultation with experts who have eld experience [10]. Generally, the AHP technique can be described through three major stages: (1) structuring a complex problem in the form of a simple hierarchy; (2) comparing decision elements using the pairwise method; and (3) computing the relative weights of decision elements [20]. This technique is, in accord with the fundamental principles of livable and ecological assessment of a city, via building up a multi-layer criteria system and allocating a standard value and numerical weight to each criterion, through mathematic calculation, to nally obtain numerical priorities, to determine if a city has reach the standards of being livable [21]. You, 2008, Luo, 2009, and Liu, 2017, Liao, 2019 and Tao, 2019 have all adopted the Factor analysis method into their livability evaluation [5,18,[22][23][24] ; and Li, 2010, Saitluanga, Benjamin L 2014, Wu, 2017and Marsal-Llacuna, M(2015, have all adopted the principal component analysis method into their livability evaluation [25][26][27][28]. Factor analysis is one of the most preferred approaches for measuring urban socio-spatial differentiation. The principal component analysis is a special case of factor analysis; the technique is a multivariate data reduction method that derives a composite, or a smaller set of variables from a large set of variables. Each of the new set of variables may be thought as a super variable that represents a cluster of highly correlated variables and is able to reveal the patterns of liveability within the city [26]. Jia, 2017, Sofeska, 2017, Yin, 2018 have adopted the GIS and spatial model into their livability evaluation.
GIS can skillfully translate some di cult features that people can't handle directly. The development of communities is partly related to their spatial location. Studies have shown that people's understanding of the actual distance is affected by social background and life experience and people with different backgrounds may have different criterions for judging distance. However, in GIS, the spatial analysis can measure straight line or walk distances accurately, and this precludes inconsistent results. Generally, GIS is very good at dealing with space and location issues [29][30][31][32].
Zhao et. al. used neural networks to assess urban liveability. The neural network is a method based on arti cial intelligence, which can adjust the inter-relations among the internal nodes to process nal results [33]. Other authors such as Tan used the GLCI method to evaluate urban liveability in 2014, 2016 and 2018. This method can be applied to all cities around the world. Also its results are consistent with results the Economist Intelligence Unit & Mercer city rankings and methods [34][35][36].
Some of the unique methods used in our included studies were probably related to the year in which the theory was introduced. Therefore, we also reported the time periods which different studies were conducted in. Another explanation for the use of some methods might be that those methods were just more popular or methodologically sounder or easier to conduct. However, the methods that are used more frequently, may not necessarily be the best methods, and may have been selected due to lack of awareness about better methods. The popularity of this methods may not have been related to their quality, but instead because of fashion, familiarity or prior training [37].
We suggest aligning and comparing future indicators against the existing urban planning policies. Building on these ndings, the next step in this research is to improve and develop a set of liveability indicators that are robust, evidencebased and linked to urban planning policies. Identifying the methods which has been done in this review is just the rst step in a much larger and ongoing work aimed at improving the methods and the scienti c rigor for assessing urban liveability. We hope that this review will help to increase awareness among planners and researchers about the indicators and methods related to urban liveability. But what is more important is to identify the factors and processes that create and affect liveability, and improve the situation of world cities.

Conclusions
This scoping review identified ve main domains of indicators for measuring urban liveability. These domains include: Economic, Environmental, Domestic Security, Socio-Cultural and Political/Governance domains. Moreover, ten methods were identi ed that could be applied to evaluating liveability and help improve urban development. Although many indicators and methods of urban liveability were identi ed in this review, the majority require further development, before they can be operationalized and used consistently by health planners and policy-makers.

Competing interests
The authors declare that they have no competing interests.

Funding
Not funding.
Authors' contributions ZK conceived the study and every one authors identi ed key literature to be included within the review. ZK led the drafting of the manuscript and key discussion points with support from TY, NK and AM. NK managed the planning of the tables (with feedback from all authors), and management of references. All authors provided important intellectual contribution and guidance throughout the event of the manuscript. MM and MMF provided guidance on the presentation of the ndings and guidance on nal revisions. All of the authors contributed to criticism and revisions to the manuscript, agreeing on the ultimate version.      Figure 1 Flow chart of study selection in this scoping review  Distribution of included studies by scope and type of indicators