Developing Global Indicators forAssessing the Age-Friendliness of Cities
Pilot Survey Report
March 2014
WHO Centre for Health Development, Kobe, Japan

Executive Summary
The WHO Centre for Health Development (Kobe, Japan) is currently leading a project to develop
global core indicators for assessing the age-friendliness of cities. As part of this process, a pilot
survey of indicators, which had been selected through a prior review and expert consultation, wasconducted in 2013. The objective was to obtain a reality check of the technical and practical valuesof these indicators performed by local stakeholders who are the intended users of these indicators.
Twenty-eight responses to this pilot survey were received from 18 cities in 15 countries around theworld. As a result, 13 indicators consistently ranked high on various evaluative scores obtained fromthe survey. More than one of those indicators were in the domains of transportation, civic
participation/employment, social participation and communication/information. The qualitative
feedback on the indicators mainly focused on the need to improve the operational definitions of theindicators, the challenges in collecting data for the indicators, and the need for the core indicators tohave some flexibility to be adaptable to different contexts. The results of this pilot survey provide a
valuable input into the subsequent deliberations on specifying the core indicators.

1. Introduction
1.1 Background to Pilot Study
Ageing and urbanization are two current global trends that present policy and decision makers withunique developmental challenges. At present, ageing is primarily viewed as an issue of thedeveloped world. However, as progress and development continue in low- and middle- income
countries, the size of ageing populations will begin to increase. How well these populations age
depends on whether or not communities can effectively adjust to the specific needs of older people.
Local policies and plans should make the urban environment more adaptable to the needs of anolder population and steer urban development in a direction that promotes active ageing, that is,
the process of optimizing opportunities for health, participation and security in order to enhancequality of life as people age (WHO, 2002).
In 2007, the World Health Organization (WHO) published, “Global Age-friendly Cities: A Guide”(WHO, 2007), which was designed to support and strengthen health and social policies that are
responsive to the two converging trends of population ageing and of urbanization. Subsequently, in
2010, the WHO launched the Global Network of Age-friendly Cities and Communities1 to foster theexchange of experience and mutual learning between cities and communities worldwide. To join the
Global Network, cities must commit to continually assess and improve their level of age-friendlinessagainst a set of indicators. However, the current Guide does not specify or suggest indicators tomonitor and evaluate the progress of age-friendly interventions.
In response to stakeholders’ requests for technical support from WHO on this issue, the WHO
Department of Ageing and Life Course (Geneva) decided to develop a set of core indicators forassessing age-friendliness of cities. The WHO Kobe Centre (WKC) is leading this initiative, applying its
expertise in urban health metrics development.
As a first step, the WKC conducted an extensive review of scientific literature, grey literature andwebsites of relevant indicator projects to compile a master list of existing indicators related to this
topic. This resulted in a list of 195 indicators which correspond to the eight domains described in theAge-friendly Cities Guide (Outdoor Spaces and Buildings, Transportation, Housing, Respect and Social
Inclusion, Civic Participation and Employment, Social Participation, Community and Health Services,
and Communication and Information), as well as an additional domain of Health (risk factors andoutcomes). In August 2012, in St. Gallen, Switzerland, the WKC brought together experts on ageing
and metrics, Age-Friendly Cities (AFC) Network representatives and WHO officials, with the main
objective of identifying a short list of potential core indicators that could be used to evaluate andmonitor the age-friendliness of cities at the local level, using the master list as the main source of
input.
The outcome of this first consultation was a list of 61 indicators across the aforementioned eight AFC
domains described in the Guide and three additional domains suggested by the expert group: Health,Economic Security, and Governance. The expert group recommended that these indicators befurther assessed in a pilot study by local health officials and other community representatives (i.e.
the intended end-users of the core indicators) based on a set of technical and practical criteria which
the experts also proposed (WHO, 2012).
1

For more information on the Global Network: http://www.who.int/ageing/age_friendly_cities_process/en/index.html

1This report presents a brief overview of the methodology used to conduct the pilot study and theresults. The report highlights major findings and priority issues which emerged from the pilot study.
These results will feed into subsequent rounds of deliberations about selecting the core indicators.

2. Methodology
A modified Delphi method is being used to develop the core indicators for AFCs. The Delphi method
is an expert survey conducted in two or more rounds in which the results from the previous roundare provided as feedback for the next. The key to the Delphi method is the anonymity provided by
the elicitation of individual opinions outside of large discussion groups. This reduces the effect ofcertain biases, such as response bias and dominance bias (Brown, 1968; Hsu, 2010). In this indicator
development project, instead of using the same panel of experts and officials throughout the entire
process, each round consists of a different panel, including some of the same exerts from a previous
round.
The indicator pilot study was part of this process (i.e. Round 2; Refer to Figure 1 to view the
breakdown of the modified-Delphi process used by WKC). It was derived from the inputs received
from the previous consultation meeting, and it elicited inputs from a new panel of survey
respondents. The objective of the pilot study was to obtain realistic assessments of the proposed
indicators by local health officials and community members. This is to ensure that the final selectionof indicators and domains takes into account the perspectives of the intended end-user groups (i.e.
local health officials and community members). Below is a summary of the methods employed todevelop, implement and analyse the results from the AFC indicator pilot study.

2

Figure 1: Process outline of the WKC modified-Delphi method
Note: The gray colouring and dotted line outlining Round #4 indicates that this step has not yet been completed
as of January 20143

2.1 Pilot Instrument development and implementation
Results from the first round of discussions at the consultation meeting in St. Gallen, Switzerland
produced a list of 61 indicators across the eight original AFC domains, plus three additional domains
suggested by experts; Health, Economic Security, and Governance (WHO, 2012). Based on the inputs
obtained from the first consultation meeting, a survey tool aimed at testing the relevance andappropriateness of the 61 indicators was developed for the pilot study.
One page in the piloting instrument was designated to each indicator (Refer to Annex 1 for sample
page from piloting instrument). Each page was divided into three sections which set out thefollowing:
1. Indicator definition - this included a proposed definition, which was derived from standard
definitions, if available; a space to enter alternative definitions for the indicator that may
have been used or preferred by local authorities; and a space to enter actual numericalvalues for the indicator for the pilot site, if available. (Please refer to WHO (2012) for thecomplete list of indicator sources and definitions.)
2. Characteristics of indicators – respondents were asked to rate each indicator on a 3-point
scale (“Yes”, ”Partly”, ”No”) based on five technical criteria (measurability, validity,
replicability, sensitivity to change, availability of disaggregated data) and five practical
criteria (alignment with local goals, implication for action, within local influence, ease oftimely data collection, social acceptability). (Explanations of each criteria can be found in thepiloting instrument.)
3. Additional comments – a space for respondents to provide any additional comments.
Starting in January 2013, pilot surveys were emailed by the WKC to individuals identified throughprofessional networks to participate in the piloting of the first draft of core indicators. Local
government officials as well as civil society members with experience or interest in Age-friendly City
initiatives were sought. Individuals that agreed to take part were requested to self-complete thequestionnaire.
2.2 Data management and coding
Between May and December 2013, twenty-three surveys representing 17 cities from 14 countries
were received. In addition to the completed pilot instruments, WKC received general comments by
e-mail regarding the list of indicators and domains, including suggestions for additional indicators oralternative definitions. In some cases, the response was representative of the opinions of officials
from multiple cities, such as in the case of the collective response from local health officials
representing over 23 local city/prefectural governments in Japan. Thus, in total, WKC received
feedback from 28 participants in at least 18 cities (but representative of over 40 cities) across 15
countries. A full list of respondents which includes country, city, and institution/organization name isavailable in Annex 2.
Pilot survey responses were manually entered into an Excel spread sheet. The responses to theindicator ratings were coded as follows in order to convert them into quantitative data:
1. “Yes” = 2
2. “Partly” = 1
3. “No” = 0
4

13

15

17

19

21

23

Outdoor spaces and buildings
Transportation
Housing
Respect and social inclusion
Civic Participation and Employment
Social participation
Community and health services
HealthCommunication and information
Economic security
GovernanceNote: Domains are listed in order of how they appeared in the survey. Each marker represents the response rate for a specificindicator within each domain. The black line indicates the mean minus one standard deviation.

Figure 2: Mean item response rate (number of actual responses out of a possible 23) for each of
the 61 indicators across the 11 domains

Note: The first five criteria listed are the Practical Criteria. The bottom five criteria listed are the Technical Criteria. The black line
indicates the mean minus one standard deviation.

Figure 3: Mean item response rate (number of actual responses out of a possible 23) averaged
across each of the ten assessment criteria
5Criteria that were not marked were coded as missing values. Standard procedures for data cleaning
and checking were performed. Item response rates were calculated by domain, by indicator, and byindividual assessment criteria.
Overall, there was a visible decrease in the item response rate (i.e. number of actual responses to aquestionnaire item, out of a possible 23) in the latter sections of the survey (Figure 2). In addition,
there was a difference in item response rate between individual indicators within a domain.
Across the ten indicator assessment criteria, the one on “possible to disaggregate” had the lowest
response (Figure 3). Otherwise, there was little variation among the mean item response rates
across the ten criteria, which were generally around 20 responses out of a possible 23.
Figure 4 illustrates the data preparation and analysis process for the open-ended comments fromthe pilot study. This qualitative information was of three broad types. The first type was indicatorspecific comments, the second type was general comments about the indicators, not specific to any
indicator, and the third type was alternative indicators suggested by the respondent. In addition,
general comments sent by email were added to the database. Personally identifiable information,such as names, was removed to anonymize the data.

Figure 4: Process for data preparation and analysis of open-ended pilot survey comments

Themes for coding the qualitative comments were determined by reviewing the open-ended
comments in detail and over multiple times. This allowed key issues and themes to be identified.
Four key themes emerged through this process, which were then used for the coding process:

6

1.
2.
3.
4.

Definition improvement
Data availability
Alternative definitions
Local characteristics

All of the comments related to the original list of 61 indicators were then coded according to thesefour themes. The same process was applied to the general comments, not pertaining to a specificindicator, which were received from participants by email as well as those from the survey.
Comments that could not be classified under any of the four themes were left aside for further
consideration during the analysis stage. Finally, comments were consolidated by theme and thensorted by the indicators to which they specifically referred (only applicable to the indicator-specificcomments), by city and by country.
2.3 Data analysis
Table 1 lists all participating cities of the pilot study, the type of feedback they provided, and thetype of analysis into which their feedback was incorporated.
Table 1: List of participating cities, type of feedback received, and their inclusion in the quantitative andqualitative data analysis

City/Institution*

7

Type of feedback

Quantitative
analysis

Qualitative
analysis

La Plata, Argentina

 Survey response✔

✔

Melbourne, Australia

 Survey response✔

✔

Ottawa, Canada (Citygovernment) Survey response General comments
 Alternative indicator list✔

✔

Ottawa, Canada(Council on Ageing of
Ottawa) Survey response General comments
 List of data sources Alternative indicator list✔

✔

Ottawa, Canada(Individual researcher) Survey response✔

✔

Public Health Agency ofCanada Survey response General comments✔

✔

Shanghai, China

 Survey response✔

✔

San Jose, Costa Rica Survey response✔

✔

Besancon, France Survey response✔

✔

Dublin, Ireland (Ageing
Well Network) Survey response✔

✔

Dublin, Ireland (Dublin
Age Friendly City
Programme City Council)

 Survey response✔

✔

Dublin, Ireland(Representative of theNorth Eastern Region of
Dublin) Survey response✔

✔

City/Institution*

Type of feedback

Quantitative
analysis

Qualitative
analysis

Dublin, Ireland (Fingal
Local Authority)

 General comments

Kilkenny, Ireland Survey response✔

✔

Akita, Japan Survey response General comments✔

✔

Japan Gerontological
Evaluation Study, Japan

 Results of own collective
ranking of the indicators

Nairobi, Kenya

 Survey response General comments✔

Jejo-Do, Korea

 Survey response✔

Seoul, Korea

 Survey response✔

Tuymazy, Russia

 Survey response✔

National AFC Programme,
Spain General comments

Wellawaya, Sri Lanka

 Survey response✔

✔

WHO Country Office of Sri
Lanka

 Survey response General comments✔

✔

Manchester, United
Kingdom Survey response General comments✔

✔

Sheffield, United Kingdom

 General comments✔

American Association of
Retired People, USA

 General comments✔

Bowling Green, Kentucky,USA Survey response✔

✔

Portland, Oregon, USA

 Survey response List of data sources

✔

✔

✔

✔

✔

✔
✔

*In some cases inputs were received from multiple sources from the same city or institution. The different respondents fromthe same city are noted where possible.

Quantitative analysis
The following quantitative analysis was applied to the data obtained from the 23 completed survey
questionnaires. The types of scores and rankings generated are shown in Figure 5.

8

Figure 5: Types of scores and rankings generated for the quantitative analysis

The basis for the score calculations was the 3-point (0, 1, 2) scale which survey respondents used torate each indicator on ten criteria, respectively. First, a sum score was calculated as the sum of
points given to an indicator by all 23 respondents. Thus, the possible range of a sum score for a given
indicator was 0 to 460. The sum score for each domain was the sum of points given to all theindicators within a specific domain. The possible range of a sum score for a domain depended on thenumber of indicators within a given domain. Secondly, an average score was calculated as thearithmetic mean, or simply the average, of the sum of points given to an indicator divided by the
number of valid responses (i.e. non-responses were excluded from the denominator). The averagescore was also calculated for each domain by taking the mean of the average scores of the indicators
within a domain. The possible range of an average score for a given indicator or a domain was 0 to 2.
Compared to sum scores, average scores are not as influenced by the variation in response rates
across indicators and criteria, nor by the differences in the number of indicators per domain whencalculating domain scores. Finally, Technical and Practical scores were separately calculated bytaking the sum of scores given to an indicator across the five Technical criteria and across the five
Practical criteria, respectively. Technical and Practical scores were also calculated using averagescores, and also computed by domain.
Based on each type of score, several rankings were performed: ranking of all indicators, ranking ofindicators within each domain, and ranking of domains. For purposes of narrowing down the list of
potential core indicators, those that consistently ranked within the top 50% of Overall, Technical andPractical score rankings, using the sum scores as well as the average scores, were highlighted aspriority indicators.

9Qualitative analysis
The qualitative analysis was applied to all the written responses to the open-ended questions in thesurvey as well as additional comments received by e-mail. To reduce error and bias, two researchers
independently coded and analysed the qualitative data. Any discrepancies were resolved throughdiscussion of the two researchers and, if necessary, a third person.
The analysis focused on identifying common issues that emerged within the four main themes alternative definitions, data availability, definition improvement and local characteristics. In the caseof the theme on data availability, the comments were further coded using the following
subcategories to capture some notably recurrent issues within this theme: “data availability”, “dataaccessibility at local level” and “requirement of a customized survey”. Comments related to thetheme of local characteristics were stratified by indicator and by city to identify which specific city
context to which they referred.
For the comments coded as relating to the theme on alternative definitions, all alternative
definitions suggested for an indicator were examined to identify any frequently mentioned ones
among them. They were also checked against the definitions used for other related indicators
included in the pilot survey to identify potential duplicates. Specific suggestions on how to improveindicators were also highlighted. In addition to analysing these responses, such concrete suggestions
were noted to be taken into consideration at a later stage in refining the operational definitions forthe core indicators.
All other comments that were not coded as being related to one of the four main themes were also
analysed to find any other recurrent issues.

3. Results
3. 1 Quantitative findings
Based on the sum scores analysis, a total of 21 indicators spanning across all domains, except in thedomains of Economic Security and Governance, were consistently ranked in the top 50% across thethree indicator rankings (i.e. Technical, Practical, Overall) (Annex 3). The top five ranking domains,from highest to lowest overall score, were Outdoor Spaces and Buildings, Civic Participation and
Employment, Communication and Information, Transportation, and Social Participation.
The results based on the average scores showed a somewhat different set of 21 indicators fromacross all domains, except Housing, Respect and Social Inclusion, and Economic Security, which
consistently ranked in the top 50% across all three indicator rankings (Annex 3). The top fivedomains, from highest to lowest overall score, were Communication and Information, Outdoor
Spaces and Buildings, Social Participation, Governance, and Civic Participation and Employment.
Indicators that consistently ranked high across all three ranking categories in terms of both the sumscores and the average scores are presented in Table 3.

10Table 3: Indicators which consistently ranked in the top 50% across all three rankings (Technical, Practical and Overall)based on both the sum scores and the average scores

DomainOutdoor Spaces and Buildings

Transportation

Civic Participation and
Employment

Indicator

Definition

Accessibility of public toilets

Perceived accessibility of public
toilets when outside of the home(among older residents*)

Frequency of public transportationuse

Self-reported frequency of trips taken
on public transportation (by older
adults)

Quality: Accessibility of buses forpeople with disabilities

Proportion of buses which are madeaccessible for people with disabilities

Availability of priority parking

Availability of priority parking areas
provided close to buildings andtransport stops

Volunteering (A): Engagement

Proportion of older residents who
engage in volunteer activities

Volunteering (B): Satisfaction

Proportion of older residents who
feel satisfied with availability ofvolunteer opportunities for older
peopleProportion of older residents withpaid employment

Paid employment rate
Culture and sports activity

Social Participation
Frequency of participation

Community and Health Services

Accessibility of home-based care
and assistance

HealthRisk factor: Physical activity

Availability of information on
leisure/recreation

Communication andInformation
Availability of information on
health concerns and service needs

Proportion of older residents who
participate in sports activities
Proportion of older residents who
regularly participate in social
activities
Proportion of older residents who
received in their own home any kindof health care or assistance fordomestic tasks they could not
perform due to health problems
during the last 12 months
Proportion of older residents who
engage in daily or weekly physicalactivity
Whether or not the local government
publishes resource guide(s) on
leisure-recreation programs that areaccessible and tailored to older
peopleWhether or not the local government
provides a source of information
about health concerns and service
needs that are accessible and tailoredto older people*”Older residents” was operationally defined in the pilot survey as someone 65 years of age or older.

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Most of these high-ranking indicators and domains tended to be rated higher on the practical
criteria than on the technical criteria. On the other hand, lower-ranking indicators and domains, aswith most of them in general, scored relatively higher on the technical criteria than on the practical
criteria. This suggests that the majority of high-ranking indicators and domains were considered to
be of more practical value (e.g. relevant to current local policies and goals), but with some technicalchallenges (e.g. lack of relevant and valid existing data) to be used for monitoring and evaluating
age-friendly interventions.
3. 2 Qualitative findings
Four key themes emerged from the analysis of indicator-specific comments.
a. Definition improvement
Most open-ended comments revolved around further clarification of numerator and denominator in
the operational definitions of the indicators. Participants felt that subjective terms, such as“suitable”, “acceptable”, or “too far”, needed to be clearly defined in order to make the indicators
more measurable, accurate and comparable. There were a number of issues with indicatordefinitions that included multiple clauses, elements or concepts (i.e. compound definitions).
Respondents noted that this could actually hinder data collection and analysis, and reduce theusability of indicators in different cities. Another common concern was regarding the apparent lackof relevance of certain indicators to the concept of age-friendliness, or whether the indicator could
be linked to an appropriate action or intervention.
b. Data availability
Comments concerning data availability centered on whether or not data were available, easily
accessible at the local level, spread across multiple sources (e.g. shared between both the public andprivate sector), or a custom survey would be required. In addition, some respondents felt it would
be difficult to obtain disaggregated data, and that within the current economic climate, developing a
new survey or replicating past surveys would be difficult.
c. Alternative definitions
Alternative definitions were usually proposed based on participants’ own experience using similar
indicators in their city assessments. In rare cases, participants proposed new definitions when theyfelt the indicator concept was appropriate but the wording of it was not quite relevant to their local
context. In addition, alternative definitions given by most participants defined the elderly population
using an age cut-off of 50 or 60, which was lower than the 65 year-old cut-off used in the pilot study.
d. Local characteristics
The fourth theme that emerged consisted of concerns related to specific local circumstances. These
comments focused on the issue of how specific weather/seasonal patterns, geographic locations,cultural norms and values, or city socio-economic/development levels affect the relevance ofdifferent indicators.
General remarks received by participants reiterated indicator-specific concerns. In particular,comments emphasized the need to improve definitions, and the challenges in collecting or accessing
12

data, including the fact that many of the proposed indicators would require a new survey which islikely to be costly. In addition, several participants made the following recommendations:







To further disaggregate data by age groups beyond the standard definition of the elderly
population as “65 and over”, in order to obtain a more nuanced understanding of the older
population
To select indicators that better measure and encourage progress towards active ageing, as
defined by WHO
To ensure a mixture of indicators in the core set that measure short-, medium-, and longterm outcomes of interventions and policies
To allow flexibility of the indicators to be able to account for variations in size of city, data
availability, and local priorities for addressing ageing and health issues
To account for the differences between developed and developing countries in terms ofageing, health and development (e.g. definition of the “elderly population”)

While this report only presents the summary of findings, the detailed comments will also be
revisited in the process of refining the core indicator set and their definitions.

4. Implications for the selection of core indicators for Age Friendly Cities
Preference should be given to indicators already grounded in existing data. Indicators which are
already routinely collected, either administratively or otherwise, generally have a pre-establisheddegree of validity and reliability, which in turn lends credibility. It also provides a baseline forcomparisons across time and place. Furthermore, developing and implementing new surveys would
be very costly and time consuming. This preference, however, creates a hindrance for themeasurement of many of the subjective or attitudinal indicators or relatively novel concepts, which
are often not available from routine sources. While public views and innovation are important toconsider in policy and intervention development, the pilot survey results indicate that it would not
be a realistic expectation for cities with many competing priorities to conduct new surveys focusing
on age-friendliness. Thus, indicators that can be obtained or generated from routinely available data
sources are preferred.
Preference should be given to indicators which possess a good balance between technical andpractical strengths. The core indicators should be technically sound but also feasible to measure andrelevant to the local context. The higher ranked indicators in the pilot study did not always have thisperfect balance. Ways of rectifying technical and/or practical shortcomings of an indicator should besought, for example, through modifications in the proposed indicator definitions.
Indicator definitions should be refined to provide better clarity. The pilot study results identified
several indicators which require improvement of definitions, especially those compound definitions
which touch upon more than one issue. The clarity of definitions will affect the accuracy ofmeasurement as well as the availability of data. In addition, clearer definitions would make theindicators more understandable by a larger number of people. This is especially important forcommunicating about the indicators with individuals who either have little knowledge regarding theconcept of age-friendliness and active ageing, or for whom English is not their native language.
Indicators should be adaptable to different urban environments. While population ageing iscurrently most advanced in the more developed parts of the world, the trends of ageing and13

urbanisation are affecting both the developed and developing areas, albeit to varying degrees.
Feedback obtained in the pilot study, especially from the developing regions, revealed the need toensure that the core indicators have the flexibility to be adapted to urban environments at different
stages of development and population ageing. Another key factor that should be taken into
consideration is the cultural context surrounding ageing. Different countries may find different
indicators to be more socially and locally relevant based on their social norms and values. Even
within the same country or city, there may be such variations among sub-population groups (e.g.
racial or ethnic minorities).
Indicators should encourage progress and be linked to an appropriate action. The pilot study
results indicated that some of the proposed indicators do not have clear links to, or implications for,action and are not suitable for measuring progress. Pilot study respondents were primarily
concerned with the indicators worded in a “Yes/No” format which are not sensitive to varying
degrees of implementation or achievement, and, thus, do not easily translate into progressive stepsof action. Many respondents agreed that such indicators may be easier to measure in some cases,
but would not necessarily encourage action or progress. The core indicators should account for themilestones toward becoming an age-friendly city and include a mixture of short-, medium-, and longterm indicators which would allow cities to assess the course of gradual progress.
4.1 Limitations
This section notes some of the limitations of the methods used in this pilot survey.
First, as described in the Methods, there was a noticeable decrease in the item response rate
towards the latter part of the survey (Figure 2). This could be due to a number of different issues,
such as survey fatigue, less interest or understanding of the domains and indicators listed later inthe survey instrument (the newly suggested domains were listed last), or a misunderstanding of thesurvey instrument format and requirements. The item response rate also varied among the 10
assessment criteria with the one on availability of disaggregated data having the lowest number of
responses across all indicators (Figure 3). Qualitative comments did reveal that participants would
skip certain criteria or an indicator if they felt it was inappropriate or that it was not relevant to theircontext. These varying response rates may have impacted the results, although it is not clear in what
way they would have biased the results.
Second, a number of participants stated they did not completely understand the indicator
characteristic rating system (3-point scale of “Yes”, “Partly” and “No”), particularly with regard to
the response, “Partly”, in the pilot survey. Some participants avoided using this response, and onlyused “Yes” or “No”, or otherwise did not provide a response. This misunderstanding of the rating
system may have also had some unknown impact on the results.
Third, the participating cities were not evenly representative of the various geographic,socioeconomic, demographic and cultural contexts of cities experiencing population ageing acrossthe world. The cities and institutions which provided feedback were located across fifteen countries,
mostly in the highly developed parts of the world: five in Europe (France, Ireland, Russia, Spain, UK),
four in the Americas (Argentina, Canada, Costa Rica, USA), four in the Western Pacific (Australia,
China, Japan, Korea), one in Africa (Kenya), one in South East Asia (Sri Lanka) and none in the Eastern
Mediterranean region. This partly reflects the higher level of interest and experience in issues
related to ageing in cities, or ageing in general, in some parts of the world compared to others.
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Furthermore, multiple responses to the survey were submitted by cities like Ottawa (Canada) andDublin (Ireland), three from each city. These multiple responses allow a richer understanding of theissue in that particular context (for example, when the responses came from both government andnon-government entities). However, since none of the responses were given differential weights
when included in the overall analysis, some cities/countries are over-represented in the data, andthus, caution must be taken in interpreting the findings.
Finally, there was an uneven representation of domains in terms of the number of indicators. In thedraft list of core indicators proposed by the expert group at the first consultation in August 2013,
and which were included in the pilot study, the domains of Community and Health Services andRespect and Social Inclusion each had the highest number of indicators, which was eight, while thedomain of Economic Security had only two indicators, the lowest number of indicators for any
domain. The disparities in domain representation by indicators influenced the comparability of thescoring and ranking of domains, and also affected the amount of both quantitative and qualitative
information that could be used to assess the domains.
It should also be mentioned that some of the pilot study respondents expressed concern about theapplicability of the indicators to rural contexts. While this may have been viewed as a limitation of
the pilot survey design, the primary objective of the broader project is to develop a core set ofindicators to assess the age-friendliness of urban settings; thus, it is by design that the indicators are
generally more applicable to urban than to rural settings.
4.2 Guidance for further selection of core indicators
Taking into consideration the final observations of the quantitative and qualitative results of thepilot study presented in this document and their implications, the following guidance is suggested
for further selection of core indicators:
1.
2.
3.
4.
5.
6.

Aim to select a total of 10-20 core indicators
Select one or two indicators representing each of the domains
Select from among the high-ranking indicators in each domain
Select at least one indicator that can be globally comparable
Select indicators that are likely to have data disaggregated by age group
Identify indicators that may not be recommended for inclusion in the core set but arenevertheless highly recommendable

5. Conclusions
As the global population continues to age in an increasingly urban world, cities and local policy
makers will be presented with a number of new and unique challenges in the 21st century. WHO
encourages cities and communities to implement age-friendly initiatives as one approach to dealing
with such challenges. This report, which presents the final results of a pilot survey of indicators for
Age-friendly Cities, provides a key input to the ongoing process of developing a core indicator set. It
builds upon previous inputs received through an expert consultation, and captures a broader rangeof perspectives from people representing the intended end-users of the indicators. The further
selection of core indicators should be guided in part by this report, with the aim to choose a
relatively small set of indicators which are adaptable to varying urban environments for assessing

15

the current situation, monitoring and evaluating interventions, measuring progress and planning
future action.

6. References
1. Brown B, Bernice (1968). Delphi Process: A Methodology Used for the Elicitation of Opinionsof Experts. Santa Monica, CA, USA: Rand Corp; 1968.
2. Hsu, Hui-Chuan et. al. (2010). “Constructing area-level indicators of successful ageing in
Taiwan,” Health and Social Care in the Community 18(1): 70-81.
3. World Health Organization, 2002. Active Ageing: A Policy Framework. Madrid, Spain: The
Second United Nations World Assembly on Ageing.
4. World Health Organization, 2007. Global Age-friendly Cities: A Guide. Geneva, Switzerland:World Health Organization.
5. World Health Organization, 2012. Meeting on Developing Indicators for the Age-Friendly
Cities Network - A Review of Ageing-Related Indicators. Background paper. Kobe, Japan:
World Health Organization Centre for Health Development.

16

7. Annexes
Annex 1: Sample page from pilot study survey questionnaire

17Annex 2: Additional information about the pilot study participants
Country
Argentina
AustraliaCity
La Plata
Melbourne

Institution
IsaludCity of Melbourne
City of Ottawa
The Council on Aging of Ottawa

CanadaOttawaThe International Longevity Centre (Riode Janeiro, Brazil)

China

N/A
Shanghai

Costa Rica

San Jose

FranceBesancon

DublinIrelandPublic Health Agency of Canada
Jing'an District Health Bureau Shanghai
Hospital Nacional de Geriatría yGerontología
Ville et CCAS de Besancon
Dublin Age Friendly City Programme City
Council
Ageing Well Network (representing
Eastern Dublin)
Individual researcher** (representing
North Eastern Dublin)

K EY PARTNERING INSTITUTIONS *The Council on Aging of Ottawa

The City of Ottawa

Public Health Agency of Canada
City of Ottawa

The Council on Aging of Ottawa

The International Longevity Centre
Canadian Mortgage and Housing Corporation
Consejo Nacional de la Persona Adulta Mayor

Dublin City Council

Dundalk Institute of Technology
NUI Maynooth
DCU





Local Government
Health Service Executive
Law Enforcement

Fingal Local Authority (representing
Northern Dublin)
Kilkenny

Nairobi(Korogocho Slum)
Jeju
Seoul
Tuymazy
N/A

City of Akita, Welfare and Health
Department, Elderly Welfare Unit
Japan Gerontological Evaluation Study(JAGES)***
African Population and Health ResearchCenterJeju Development InstituteSeoul Welfare Foundation
Organization of Retired Persons
National Age-friendly City Programme

Wellawaya

Uva Provincial Council

N/A

World Health Organization, Sri Lanka
Country Office

Akita
Japan
N/A
Kenya
Korea
RussiaSpain

Sri Lanka

UnitedKingdom

United Statesof America

Ageing Well Network

Sheffield
Manchester

Sheffield City Council
VOP, Public Health Manchester,Manchester City Council

Bowling Green,
Kentucky

City of Bowling Green

Portland, Oregon

Portland State University - Institute on
Aging

Centre for Wellbeing and Society, Nihon Fukushi
University (JAGES Secretariat)







Ministry of Social Services
Ministry of HealthUva Provincial Council
Ministry of Health
Ministry of Social Services








University of Manchester
UK Urban Ageing Consortium
Western Kentucky University
City of Bowling Green Neighborhood
AARP Kentucky
City of Portland Bureau of Planning andSustainability
Multnomah County Aging and Disability
Services Division
Metro
Portland's regional government





N/A
American Association of Retired People*Key partnering institutions as mentioned by the survey respondent.
**Individual respondent’s names are not revealed in order to protect their privacy.
***JAGES provided the collective response of a total of 38 local health officials representing 23 local city/prefectural governments fromacross Japan.

18

Annex 3: Indicators which consistently ranked within the top 50% of Overall, Technical and Practicalscore rankings based on sum and average scores, respectively
SUM SCORE RANKINGOVERALLR ANKTECHNICALR ANK

P RACTICALR ANKWalkability

2

8

1

Neighbourhood safety

22

18

17

Accessibility of public
toilets

6

18

9

Accessibility of publicbuildings

15

15

2

Frequency of public
transportation use

96

Quality: Accessibility ofbuses for people withdisabilities

8

9

Civil Participation and
Employment

Respect and Social Inclusion

Housing

Transportation

Outdoor Spaces andBuildings

DOMAIN I NDICATOR

19

AVERAGE SCORE RANKINGOVERALL
I NDICATORR ANKTECHNICALR ANK

P RACTICALR ANKAccessibility of public
toilets

17

28

14

13

Frequency of public
transportation use

18

8

26

7

Quality: Accessibility ofbuses for people withdisabilities

6

4

10

Quality: Accessibility oftransportation stops
from home

19

25

22

Availability of priority
parking areas

11

21

11

Availability of priority
parking areas

11

14

6

Choice: Proportion ofolder residents byhousing type

12

3

20

Policy exists to guidethe planning of new
housing constructionthat ensures
accessibility

16

17

10

Ageism: Older residents
feeling alienatedbecause of their age

13

5

19

Positive relations: Older
residents’ satisfaction
with availability ofopportunities tointeract with younger
people20

19

14

Volunteering (A):Engagement involunteer activities

1

4

4

Volunteering (A):Engagement involunteer activities

2

2

9

20

8

30

9

1

28

Volunteering (B): Older
residents’ satisfaction
with availability ofvolunteer opportunities
for older people

10

2

16

Volunteering (B): Older
residents’ satisfaction
with availability ofvolunteer opportunities
for older people

Paid employment rateof older residents

4

1

18

Paid employment rateof older residents

SUM SCORE RANKING

Communication and Information

HealthCommunity and HealthServices

Social Participation

DOMAIN I NDICATOR
Culture and Sports (A):Older residents’ regularparticipation in sports
activities

Older residents’frequency ofparticipation in social
activities

OVERALLR ANKTECHNICALR ANK

P RACTICAL
R ANK

7

11

5

14

9

13

Community
Engagement (B): Older
residents’ satisfaction
with availability ofsocial gathering places

22

17

18

Accessibility (A): Older
residents’ use of homebased care/assistance

18

9

19

Risk Factor: Proportionof older residents who
engage in regularphysical activity
Local government
publishes aleisure/recreation
resource guideaccessible and tailoredto older people

Local government
provides information,accessible and tailoredto older people, about
health concerns andservice needs

20

14

3

17

17

10

15

8

3

AVERAGE SCORE RANKINGOVERALL
I NDICATORR ANK
Culture and Sports (A):Older residents’ regular3
participation in sports
activities
Culture and Sports (A):Older residents’ regular25
participation in culturaland arts activities
Older residents’frequency of
8participation in social
activities
Life-long learning: Older
residents’ enrolment in
26
formal education
Community
Engagement: (A); # whohave access from their
12
home to a community
centreP RACTICAL
R ANK

7

6

29

21

3

15

26

24

20

12

Accessibility (A): Older
residents’ use of homebased care/assistance

12

9

18

Health (B): Proportionof older residents withfunctional limitations

23

11

29

Risk Factor: Proportionof older residents who
engage in regularphysical activity

15

14

19

4

15

2

7

23

7

1

10

1

27

22

27

Local government
publishes aleisure/recreation
resource guideaccessible and tailoredto older people
Local government
provides information
about employment andvolunteering
opportunities for older
peopleLocal government
provides information,accessible and tailoredto older people, about
health concerns andservice needs
Older residents’satisfaction withcomputer and internet
access in public spaces

20

TECHNICALR ANK

SUM SCORE RANKING

Governance

DOMAIN I NDICATOR

N/AOVERALLR ANKTECHNICALR ANK

P RACTICALR ANKAVERAGE SCORE RANKINGOVERALL
I NDICATORR ANKResources: Proportionof local government
spending on health

5

TECHNICALR ANK

P RACTICAL
R ANK

13

3

Note: The highlighted (shaded) indicators are those which consistently ranked within the top 50% of Overall, Technical and Practical score
rankings based on both sum and average scores.

21