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Why is living in the city more attractive in some places than in others? How can policymakers, urban planners and engineers work together to make cities better places to live for urban residents? One way to understand what makes a city liveable is to examine a key measure of quality of life: individual level happiness. Recent research suggests that happiness is not simply a function of individual factors such as health, wealth and social relations. Happiness is also influenced by where people live. City residents are happier if they feel connected to their cities and neighbourhoods and feel positively about the state of city services. Using a sample of over 5000 urban residents in five major cities, this paper builds on recent findings that indicate the happiness of city residents is affected by citizen perceptions of their city as a place to live and their evaluations of the essential services provided by government and non-profit organisations. Using structural equation modelling, the authors demonstrate that latent variables tapping these perceptions have both direct and indirect influences on self-perceptions of happiness in five major cities.
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Urban Design and Planning
Untangling What Makes Cities Livable: Happiness in Five Cities
--Manuscript Draft--
Manuscript Number: UDP-D-11-00031R1
Full Title: Untangling What Makes Cities Livable: Happiness in Five Cities
Article Type: Themed issue - Quality of Life
Corresponding Author: Kevin M Leyden
West Virginia University
Morgantown, WV UNITED STATES
Corresponding Author Secondary
Information:
Corresponding Author's Institution: West Virginia University
Corresponding Author's Secondary
Institution:
First Author: Abraham Goldberg, Ph.D
First Author Secondary Information:
Order of Authors: Abraham Goldberg, Ph.D
Kevin M Leyden
Thomas J. Scotto, Ph.D
Order of Authors Secondary Information:
Abstract: Why is living in the city more attractive in some places than in others? How can
policymakers, urban planners, and engineers work together to make our cities better
places to live for urban residents? One way to understand what makes a city livable is
to examine a key measure of quality of life: individual level happiness. Recent research
suggests that happiness is not simply a function of individual factors such as health,
wealth, and social relations. Happiness is also influenced by where we live. City
residents are happier if they feel connected to their cities and neighborhoods and feel
positively about the state of city services. Using a sample of over 5,000 urban residents
in five major cities, this article builds upon recent findings that indicate the happiness of
city residents is affected by citizen perceptions of their city as a place to live and their
evaluations of the essential services provided by government and non-profit
organizations. Using structural equation modeling, we demonstrate that latent
variables tapping these perceptions have both direct and indirect influences on self-
perceptions of happiness in five major cities.
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Untangling What Makes Cities Livable:
Happiness in Five Cities
The Engineer and the City
In this article we examine how cities affect happiness. Building upon recent
research, we clarify how residents‟ perceptions of their cities as places to live and the
quality of city services contribute to the happiness of people who live in cities. Our work
seeks to emphasize that life in the city is about far more than excellent engineering or
high quality architecture. The relationships people have with one another, their access to
cultural, leisure, and shopping amenities and public transportation, the attractiveness of
the city, and the quality of government services they receive can make urban living
pleasurable or dissatisfying. Given the importance of cities for the well-being of people
and the environment, we argue there is a real need to focus upon improving the quality of
life for people who live in cities. Part of what is needed is to promote innovative linkages
between engineers, architects, city planners, policymakers, entrepreneurs, and city
residents with the goal of promoting high quality living in cities for residents throughout
the lifespan and across differing socioeconomic backgrounds.
We first discuss the environmental, social, and personal benefits that may come to
citizens when they live in well organized and managed cities. We next comment on the
standard correlates of individual level happiness in cities before proposing that citizen‟s
perceptions of life in their city may add explanatory power to models of happiness. In
our empirical section, we employ Structural Equation Models (SEMs) to test the
hypothesis that individual evaluations of urban life fall along two latent dimensions:
perceptions of the city as a Place to live and assessments of the Performance of the city
Main Text (FINAL VERSION)
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in the delivery of essential services. After operationalizing these two concepts, we find
them to have both direct and indirect influences on self perceptions of happiness among a
representative sample of respondents in five major cities.
The City as a Solution?
An intriguing and growing body of research points to the ability of cities to be a
solution to many of the problems that modern societies face. Higher density cities with
mixed-use, walkable neighborhoods may benefit us, the economy and the environment in
ways that are not readily appreciated by the public, policymakers, and those who build
our cities, such as engineers and architects. Cities where residents have easy access to
convenient public transport, social gathering places, and shops and cultural amenities
within walking distance tend to be places with a significantly lower carbon footprint per
capita, in part because the urban form does not necessitate daily car usage. Such places
can also be more healthy because residents typically walk far more and drive far less than
their suburban or rural counterparts (see Kawachi & Berkman, 2003; Frumkin, Frank, &
Jackson, 2004). Less driving and more walking can translate into less obesity in cities,
and fewer deaths and injuries due to vehicle crashes (see Saelens et. al., 2003; Frumkin,
Frank, & Jackson, 2004; Doyle, 2006). Access to more social activities tend to reduce
social isolation; cities and their urban neighborhoods can provide residents with the kind
of social opportunities that can facilitate improved physical and mental health (Brown et
al., 2008).
Interestingly, well-functioning cities may also facilitate creativity, innovation and
wealth creation (Florida, 2002, 2008; Glaeser, 2011). Cities have long enabled
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interaction among people which often leads to forms of collaboration and competition
that fosters innovation and entrepreneurship. These interactions mainly face-to-face -
lead to better art, music, fashion, conversations, restaurants and shops, universities,
innovative products, ideas, services, and new philosophies (Florida, 2002). Social
interaction, competition, and learning from others, makes smart people smarter,
uneducated people more educated and entrepreneurial types more entrepreneurial.
Economist Edward Glaeser summarizes data suggesting that cities are environments
where wealth is generated and maintained:
„Over half of American income is earned in twenty-two metropolitan areas” (p.
267).
Americans who live in metropolitan areas with more than a million residents are,
on average, more than 50 percent more productive than Americans who live in
smaller metropolitan areas. These relationships are the same even when we take
into account the education, experience, and industry of workers. They‟re even the
same if we take individual workers‟ IQ into account” (p. 6)
There is a near perfect correlation between urbanization and prosperity across
nations. On average, as share of a country‟s population that is urban rises by 10
percent, the country‟s per capita output increases by 30 percent” (p. 7). (Glaeser,
2011)
This is not to say that all cities are great places. Many have significant problems, and
are often plagued with pollution, crime, corruption, and severe poverty. Internationally,
urban locales often absorb the bulk of the homeless and the rural poor, and many contain
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large swaths of slums or abandoned homes and buildings. Many cities are the victims of
the changing nature of commerce, whereas others -especially in the U.S. - have witnessed
population declines in part due to public policies and social expectations that benefit car-
dependent suburbs and exurbs (Jackson, 1980; Levy, 2000; Baxandall & Ewen, 2000;
Duany, Plater-Zyberk, & Speck, 2000; Meredith, 2003). Cities facing population out-
migration must also endure a declining tax base that exacerbates poverty, and does little
to alleviate racial and ethnic divisions, inadequate housing policies, or improve struggling
schools (Frey, 1979; Downs, 1998; Jargowsky, 2002; Powell, 2002; Osman, Nawawi, &
Abdullah, 2008). For these reasons, and others, many residents often attempt to escape
the city for the suburbs; but suburban living has its share of problems as well.1
Despite these concerns, cities and city building remain a growth industry.
Currently a little over half of the world‟s population is urban, and this percentage is
growing. The United Nations projects that by 2030, about 5 billion people will be living
in urban areas (United Nations, 2006). This growth is particularly intense in the
developing world. It has been reported that “India, for example, will require 500 new
cities in the next 20 years to accommodate its future needs” (Kennedy, 2009, p. 37).
Contrary to what one might suppose, increased urbanism might mitigate the
forces thought to contribute to climate change and other social ills such as declining
1 Car-dependent suburban living is associated with unintended problems such as obesity, automobile
accidents, and declines in social capital (Putnam, 2000). People who do not have the means or ability to
own and operate a car, such as the poor, or elderly are especially at risk of social isolation (Duany, Plater-
Zyberk, & Speck, 2000; Helliwell & Putnam, 2005). Commuting and shopping by car (instead of walking,
cycling or taking public transport) also produces a significant amount of carbon and air pollution.
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membership in voluntary organizations, social isolation, and obesity. Negative aspects of
city life also could be mitigated by developing policies designed to improve city living
and the quality of places and amenities. It goes without saying that happier people are
less likely to abandon their cities for the suburbs, something that makes determining the
correlates of happiness an important research endeavor.
Major Findings of Happiness Research
In his well-known work, Layard (2005) describes several factors that affect
happiness among adults. In addition to income or relative financial situation, happiness
appears to be related to a person‟s family relationships, and perceptions of employment
or work status, relations with community and friends, and health.
In general, higher income is associated with greater levels of happiness. This is
especially true within countries; people judge their wealth relative to those around them
(Frey & Stutzer, 2002; Bruni & Porta, 2007). Happiness is also related to positive family-
oriented relationships. Married people, all things being equal, are happier than those who
are divorced, separated, widowed, or who have never been married (also see Huppert,
Baylis, & Keverne, 2005; Frey, 2008; Martikainen 2009; Koopmans et. al, 2010).
Employment and work status, and trust in and connections with the community
and government officials also matter. People who are employed with a secure or
satisfying job are happier than those who are unemployed or hold an undesirable job
(Layard 2005; Martikainen, 2009; Winkelmann, 2009). Additionally, Helliwell &
Putnam (2005) show that that happiness is significantly related to spending time with
friends and neighbors, civic participation, and having trust in the local police.
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Personal health is also significantly associated with self-assessed happiness
(Layard, 2005). Although the strength of this relationship depends in part on whether
overall health is measured subjectively (i.e., self-assessment) or objectively (i.e.,
determined by a doctor), a link between health and happiness is consistently
demonstrated in the literature (Frey & Stutzer, 2002; Marks & Shah, 2005; Koopmans et.
al. 2010). Personal freedom is important as well for predicting happiness; it is primarily
measured by the extent to which people feel their governments are effective and the
extent to which they live in a place that affords them meaningful rights and the rule of
law. Finally, personal values can affect individual happiness. In general people who are
care for others and the world around them are happier (Layard, 2005; see also Putnam,
2000; Frey & Stutzer, 2002; Helliwell & Putnam, 2005; Garcia et. al., 2007)
Beyond the Usual Suspects: Untangling How Place and Performance Affect
Happiness
Leyden, Goldberg, and Michelbach (2011) present a model of individual
happiness in ten urban environments using data obtained from the 2008 Quality of Life
Survey (QLS).2 They found citizen self assessments of their own happiness to be
significantly related to the factors identified by Layard (2005) and operationalized using
questions available on the QLS. Those who rated themselves high on an ordinal scale of
happiness had higher incomes, were married, believed that jobs and volunteer
2 Data collected for the 2008 Quality of Life Survey (QLS) was collected in late 2007 and was facilitated
by the generous assistance and support of the South Korean National Academy of Sciences, the Seoul
Metropolitan Government, the Global Metropolitan Forum of Seoul, and the Seoul Welfare Foundation. All
interpretations of the data contained in this study are the responsibility of the authors. Approximately 1,000
respondents over the age of 18 in each city were interviewed by telephone and stratification was used to
control for age and gender. The surveys contained identical substantive questions in addition to a limited
number of demographic indicators.
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opportunities were available in their city, felt connected to others, trusted their city
government, and had higher evaluations of their health. Beyond these forces, Leyden et
al. (2011) also noted a significant relationship between happiness and select variables in
the QLS dataset that tapped respondents‟ perceptions of their city. We improve on this
work by theorizing that multiple measures tapping citizen evaluations of their locales are
functions of two latent dimensions we label “Place” and “Performance.”
Citizen evaluations of their city‟s built environment or aspects of “Place”
facilitate the ability to enjoy life and attain one‟s daily needs; these place measures may
be a key to understanding not only happiness but health and other factors related to
quality of life. We consider measured indicators of the “Place” concept to be the QLS‟s
five point agree-disagree assessments of: a) pride in one‟s city ; b) the perception that
there are many parks and sports facilities in the city; c) the perception of easy access to
cultural and leisure amenities, such as movie theatres, museums, and concert halls; d) the
convenience of public transportation; e) the degree to which residents feel their city is
beautiful; and f) the perception that there is easy access to plenty of shops and stores. 3
The second factor, which we label “Performance,” is a measure tapping citizens‟
general perceptions of how core services usually provided by governments or non-profits
function in the city. One can imagine how dissatisfaction with local officials‟ inability to
provide basic services such as those related to health, education and safety, might lead to
reduced levels of happiness or lower levels of health or trust in government.
Hypothetical indicators of this latent factor available in the QLS are self-assessments of
the: a) ease of getting children into good schools in the city; b) perceptions that the city is
3 The survey instrument is available at either http://ipa.wvu.edu/ or
http://www.thomasjscotto.co.uk/index.php?p=1_5_Data.
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a good place to rear and care for children; c) the ease of getting good quality healthcare in
the city; d) facilities the city provides to the disabled, the elderly and the disadvantaged;
and e) the perceived safety of walking in the city at night.
Indicators of the “Performance” construct differ overall from those of the “Place”
construct because those of the former are directly linked to basic service provision (e.g.,
the quality of schools or policing) while the focus of the latter are more related to the
built environment, access to built cultural, leisure, or shopping amenities, and/or the
overall aesthetic or “look and feel of the city as a place to live. Consequently, we expect
the concepts of “Place” and “Performance” to be unique, but correlated to one another
since many of the things that create the overall sense of place or attractiveness of the city
are also linked to decisions by government and the provision of services provided by the
public sector.4
We employ Confirmatory Factor Analysis (CFA) to test whether there is a
statistically valid relationship between the hypothesized latent constructs and the survey
responses to the questions outlined above (cf. Byrne 1998). Figure 1 depicts the
measurement model we wish to test with variables in circles designed as latent and
variables in squares designated as observed. Questions of measurement invariance and
equivalence lead us to limit our analyses to QLS respondents from New York, London,
Toronto, Berlin, and Paris only.5
4 As a methodological aside, one advantage to employing Confirmatory rather than Exploratory Factor
Analysis is that the former allows the correlation between latent variables to be estimated freely rather than
depending on an imposed rotation structure. All indicators are treated as ordinal and are coded in a positive
direction so that higher scores on the latent variables equate to better evaluations of the performance of
services in a city and to the city as a place to live.
5 The QLS dataset also contains respondents from the cities of Seoul, Milan, Tokyo, Beijing, and
Stockholm. From the outset, we elected to exclude the three Asian cities because of our concerns about the
functional equivalence the self assessments of happiness and health among Asian and European/North
American respondents (for a review, see Diener and Suh 2003, and for a discussion of functional
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[Figure 1 about here]
In the CFA model, we are interested in a number of parameters and summary
statistics that we can use to describe the relationship between and among the latent
variables and their measured indicators. Following standard notation (see Hayduk 1987),
we are interested in the regression of the factors onto the responses to the survey
questions (symbolized by λxx in Figure 1), the correlation between the two factors (φxx)
and the ability of the two latent variables to explain variation in the survey responses (1-
δxx). Overall fit of the specified model to the data can be established by summary
statistics that signify whether the decisions to link the latent variables to the specific
indicators, and designating separate factors for “Place” and “Performance” are valid.
The large sample size of 5011 respondents across the five cities leads us to rely on
a measure of close fit rather than the χ2 statistic to assess performance.6 The Root Mean
Square Error of Approximation (RMSEA) can be thought of as the average discrepancy
equivalence in cross-cultural research, see Medina et al. 2009). Exploratory Structural Equation modelling
(ESEM) established the two dimensions of “Performance” and “Place” separately for five of the remaining
seven cities. However, for Milan and Stockholm, the factor loadings were significantly and substantively
different from those obtained in separate analyses of respondents from the remaining five cities. In
technical terms, the measurement models for the two cities did not have “configural invariance,” meaning
that the two factor structure with the designated loadings was an inappropriate representation of the
hypothesized concepts for these two locales (Meuleman and Billett 2011, p.186) Consequently, adding
respondents from these cities to the above pooled analyses would bias the coefficients established for the
combined models presented in the tables and figures and might lead to erroneous conclusions. Analysis of
why manifest indicators of the “performance and “place” dimensions work differently, the reason they do
so, and the correlates of the indicators with happiness in the excluded cities is beyond the scope of this
article, but remains a topic of our on-going research agenda.
6 Technically, the χ2 statistic tests whether the model specification with its restrictions (e.g. survey
questions only loading on a single factor, the absence of covariance among the δXX parameters) is true.
Bollen (1989; see also Byrne 1998: 110) interprets the probability associated with the χ2 “exact-fit” test as
the closeness of fit between a hypothesized model such as that presented in Figure 1 and the actual
variance/covariance matrix from the actual data. High sample sizes, while important to gaining efficient
estimations of the parameters of interest also makes the χ2 statistic vulnerable to random misfit, and is the
reason we rely on the “close-fit” RMSEA values to gauge model performance. Given the ordinal nature
of the data, we employ the Weighted Least Squares with Adjusted Means and Variances (WLSMV)
estimator available in the MPLUS 6.1 program to estimate model parameters based upon the asymptotic
covariance matrix.
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between the observed and model implied correlations weighted by the degrees of
freedom, and the consensus is that close fit is attained when this statistic is below 0.05
(Browne and Cudeck 1992). The RMESA obtained after estimation of the model
presented in Figure 1 is 0.04, giving us confidence that the model adequately captures the
observed relationships among the variables. Consequently, we conclude that the two
factor model specification tapping attitudes towards the respondent‟s perceptions of their
city as having a built environment that provides quality place destinations (and/or an
overall sense of place) and the performance in delivering services related to social
welfare or well-being is valid.
Not only is the model empirically justified, but the survey questions chosen as
indicators of the two latent variables all appear to be valid aspects of the concepts.
Model specification requires that a path between each latent variable and an indicator be
fixed at 1.0, and we do this for the “Pride” and “Schools” questions, and the strengths of
the remaining paths from the latent variables to the questions that get estimated can be
interpreted as relative to the two that are fixed at 1.0. The estimated path coefficients
listed in Table 1 indicate that all questions we chose to be reflections of the concepts are
significantly and substantively related to the latent variables. The indicators labeled
“Culture” and “Healthcare” have the strongest relationships to the concepts, but even the
weaker “Shops” and “Safety” variables have strong loadings. The ability of a single
latent variable to explain variation (R2) is in line with many subjective survey measures
employed in social science research. However, the slightly weak R2 of 0.19 observed for
the “Safety” indicator suggests that future work may wish to establish a question that
better relates perceptions of safety to the other indicators of city performance.
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[Table 1 about Here]
The correlation between the latent variables of 0.57 indicates that there is a clear
relationship between perception of the city as a “Place” and evaluations of the
“Performance” of key services, but the remaining unexplained co-variation also suggests
they are distinct concepts.7 The factor scores generated from the CFA, each with a mean
of approximately 0, provide us with valid and continuous variables tapping both
concepts. Our next task is to ask whether the considerable variability on each of the
latents (place s2=0.83; performance s2=0.50) influence self-assessments of happiness
across the five cities.
Happiness as an Outcome
The QLS asked all respondents whether they were “not happy at all,” “not very
happy,” “neither happy nor unhappy,” “somewhat happy” or “very happy,” and we
consider answers to this question to be the respondents‟ self assessment of their own
happiness. The ability of the Place and Performance factors to influence happiness in the
five cities can be gauged via a structural model linking the latent variables to outcome
variables of interest. In the multivariate analyses presented below, we follow a three-step
process. Respondents‟ evaluations of their own happiness are first modeled using the two
factors only. The R2 summary statistic obtained after the analysis indicates the amount of
variance in happiness explained by knowing only respondents positions on the two latent
dimensions.
7 Supplemental analyses (not shown) placing all the survey questions under a single Performance/Place
super-factor produced a model with worse exact and close fit statistics.
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The second step involves determining whether the impact of one or both factors
remains significant when variables tapping those identified by Layard (2005) and city
controls are added to the model. These controls are important given the importance
accorded to them in recent research on happiness (e.g., Leyden et al. 2011), and the fact
that there may be within-city variance in happiness that remains unaccounted for by the
other variables necessitates the dichotomous city control variables.8 We also examine
indirect effects.
Table 2 presents the results for models of individual level happiness using the
latent factors modeled above on their own and with controls. Model parameters are
estimated using ordinal probit procedures (e.g., Long and Freese, 2006). On their own,
the Place and Performance factors explain 9% of the variance in self assessments of
happiness, and the slope coefficients obtained for the latent variables are substantively
and statistically significant. The direction of the effects also accord with expectations:
city residents with higher evaluations of the performance variables in their city (or the
degree to which services are provided) and also higher evaluations of the sense of place
or built environment variables (e.g., aesthetics of the city and access to cultural
amenities) tend to have higher assessments of their own happiness.
8 Full question wording of the survey questions used to operationalize Layard‟s (2005) concepts can also be
found on the webpages referenced in footnote 3. Briefly, they are five point questions with answer choices
ranging from strongly disagree to strongly agree, which tap the: a) availability of volunteer opportunities in
their city; b) how connected respondents feel they are to people living in their neighborhood; c) presence of
job opportunities in their city; and d) level of trust they placed in their city‟s government. Respondents
were also asked to indicate whether they were married and to assess their income on a scale ranging from
“very low” to “very high.” Self assessments of overall health ranged from “very bad” to “very good.” In
the findings shown for Tables 2 and in Figure 2, the exogenous non-city controls in the model are treated as
interval level variables for presentation purposes; however, auxiliary analyses treating the measures as
nominal (employing dichotomous variables for each possible answer choice) yielded similar substantive
findings. In the analyses presented in Table 2, London is the reference category.
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[Table 2 about Here]
The two latent factors, however, are not the sole predictors of happiness. Taken
by themselves, results presented in the second column show that the variables taken as
proxies for most predictors highlighted by Layard‟s (2005) are all significantly associated
with happiness, as are three of the four country controls.9 The question then turns to
whether, above and beyond the standard predictors of happiness, our latent variables
measuring peoples‟ perceptions of their city as a Place to live and evaluations of essential
service Performance add additional explanatory power to models of happiness. Column
three of Table 2 provides an affirmative answer. The two latent variables increased the
explained variance in the dependent variable and remain significant once controls for
Layard‟s (2005) factors and respondents‟ cities are added. In short, citizen perceptions of
the place variables and the services or performance variables appear directly related to
individual evaluations of their own happiness.
What about indirect effects? Aspects of the city tapped by the two latent variables
may also have an impact on the substantive, non-socio-demographic independent
variables presented in Table 2. Although it might be a causal stretch believe that
marriage alone mediates the relationship between the latent variables and happiness, one
could imagine that those who believe their city does a good job at providing basic
services and provides an attractive built environment or sense of place also look for and
observe volunteer opportunities that are available in the city, feel connected to people
living in their neighborhoods, or think that where they live is a good place to seek better
9 The significant city controls indicate that there is within city variation in levels of happiness that remains
unexplained.
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employment. The hypothesis that the “Place” and “Performance” latent variables also
have direct effects on some of the traditional predictors of happiness as measured by
Layard (2005) and others leads to a further hypothesis that the two latent variables
derived above work through a selection of the variables presented in Column 2 of Table 2
to drive respondents‟ happiness. Combined, the direct and indirect effects of the two
latent variables might be stronger than what is suggested by the direct results presented in
Table 2.
Figure 2 presents results from an estimation of a recursive model positing that the
two latent variables have both direct and indirect effects on happiness. Estimated as a
full path model, we see the direct effects of the “Place” and “Performance” variables are
statistically significant but slightly attenuated (in comparison to the coefficients presented
in Column 3 of Table 2). However, we also find that the two latent variables have strong
and significant relationships to the “Health,” “Connected,” “Job Opportunities,” and
“Volunteer” variables. The latent variable tapping the Performance of the city in terms of
the basic services it provides is significantly related to Trust in local officials.10
[Figure 2 about Here]
A number of indirect paths between Happiness and the Place and Performance
latent variables were significant: the effect of the Performance variable working through
individual perceptions of Health was 0.06 (p<0.00), and significant effects were also
found for the paths working via the “Connected” (0.04; p<0.00) and “Volunteer” (0.01;
10 Curiously, perceptions of the city as a place to live is negatively associated with trust. The indirect effect
of both latents on happiness when they work through the trust variable is, however, insignificant.
Consequently, we leave this peculiar finding as a topic for future research.
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p<0.05) variables. The combined indirect influence of the Performance variable on
Happiness was 0.13 (p<0.00), and the total effect of the variable was 0.28 (p<0.00).11
The Place variable also had significant, but weaker, indirect effects on happiness.
Like its counterpart, the three significant indirect effects were for the paths working
through Health (0.05; p<0.00), Volunteer (0.03; p<0.00), and Connected (0.02; p<0.00).
All told, the total of the indirect effects added up to 0.11 (p<0.00), and Place‟s total effect
on Happiness was 0.25 (p<0.00).
Discussion & Conclusions
This research finds that the individual happiness of city residents is significantly
associated with their perceptions of the city as a Place to live and evaluations of the
Performance of the city in delivering vital services. The latent Place and Performance
variables not only have a direct effect on resident happiness; there are also indirect effects
as mediated by more traditional factors found to predict happiness in recent work (Layard
2005). People who consider their cities to be good “Places” (e.g., beautiful cities which
they are proud to live in, where they can attain easy access to plenty of shopping, cultural
and sport amenities, parks, and convenient public transportation) also report feeling
healthier which is found to be a significant predictor of happiness. The relationship
between “Place” and happiness is also mediated by the “social health” of the city as
measured by the level of connectedness people feel towards others along with the belief
the their cities provide many opportunities for volunteer activities. Social connectedness
11 Indirect effects with corrections for the standard errors obtained via MPLUS‟ “Model Indirect”
command. The ordinal nature of the dependent variable requires estimation by ordered probit with the
program‟s WLSMV estimator. Total indirect and direct effects also take into account the insignificant
paths shown in Figure 2.
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and volunteer opportunities are key measurements of social capital and have been linked
to happiness in previous research (Putnam, 2000; Helliwell & Putnam, 2005). Cities
perceived as good “places” can foster such connections and lead to higher levels of
individual happiness.
Beyond the importance of Place, survey respondents were asked a series of
questions tapping into the Performance of the city in providing basic services such as
good schools, healthcare opportunities, and facilities serving the disabled and
disadvantaged. There were also broader questions about feeling safe from crime and the
ability of the cities to be good environments to raise families. As with the “Place”
variables, these “Performance” variables were found to have a direct effect on individual
happiness. The “Performance” variables also had an indirect effect on happiness through
self-perceived health and “social health”. Further, the “Performance” variables were
significantly related to the perception that the city offers plenty of job opportunities. The
empirical results lead to an important normative conclusion: in respect to the happiness of
residents, the quality of life provided by cities matter, and this important finding should
be incorporated into the broader “happiness literature” that is increasingly being
conducted across the conventional walls of academic disciplines.
The above findings provide promising avenues for future work. First, additional
research should be done to explain more of the significant differences in happiness that
exists between cities, even after accounting for the contribution of cities as places and
their performance in providing services. Second, researchers should work to consider
ways that different neighborhood designs within cities might affect happiness. We
suspect that within the same city, neighborhoods that are walkable with a vibrant
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streetscape and sense of community are more likely to positively affect happiness than
car-oriented design models. Third, work should be done to identify cities that have
created policies to positively impact the happiness of residents and track their
effectiveness over time. This would afford an opportunity to create specific policy
prescriptions for cities to consider.
Our findings indicate that in cities key aspects of the places we build and the
services we provide are very important to the lives of residents. The ability of cities to
offer place amenities and provide meaningful services that people value not only directly
affect happiness; they are also significantly associated with other factors important to
happiness such as health and social connectedness.
These findings come at a time when most cities around the world are
projected to experience exponential growth and as world leaders and are
increasingly using measurements of well-being to evaluate their culture and
society (Stiglitz, Sen, & Fitoussi, 2009). The attractiveness or beauty of cities, the
convenience of public transportation, and the availability of key cultural, sport,
and shopping amenities as well as the quality of city services are shared
responsibilities among many groups including engineers, architects, business
leaders, and government policymakers. It is human decision making, not random
chance, that determines the success or failure of cities to provide opportunities for
residents to have a successful and meaningful quality of life.
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Figure 1: Measurement Model Linking “Place” and “Performance” Latent Variables to
Observed Survey Question Responses
λ41
λ51
λ31
λ21
λ61
1
λ82
λ92
λ10.2
λ11.2
δ66
δ55
δ44
δ33
δ22
δ11
δ77
δ88
δ99
δ10.10
δ11.11
φ21
Figure (FINAL VERSION)
1
.60*
.15*
.15*
.08*
.30*
.21*
.45*
-.13*
.12*
.13*
.83*
.57*
.21*
.20*
.49*
.01
.06*
.03
Notes: *=p<0.05; City Fixed Effects
Not Shown
Figure 2: Direct and Indirect Effects of Place and “Performance” Latent Variables on Happiness
Table 1: Combined Confirmatory Factor Analysis Establishing the Construct Validity of
Place and Performance Latent Variables across 5 Cities.
Notes: All estimated coefficients significant at p<0.05. †=Fixed parameter. Model fit: χ
2
WLSMV
=423.53 (43df);
RMSEA=0.04; TLI=0.97.
Place
Performance
R2
Pride
1.00
0.45
Parks
0.81
0.35
Culture
1.14
0.52
Transport
0.70
0.29
Beauty
0.79
0.34
Shops
0.70
0.29
Schools
1.00
0.33
Raise Child
1.00
0.33
Healthcare
1.11
0.38
Disadvantaged
0.97
0.32
Safety
0.68
0.19
Place/Performance
Correlation
0.57
Place
Performance
Mean
0.00
0.00
Variance
0.83
0.50
Tables (FINAL VERSION)
Click here to download Table: Untangling What Makes Cities Livable Tables 1 and 2 (FINAL).doc
Table 2: Regression of Self Assessed Happiness onto Latent Variables and Layard’s
Predictors
Note: Standard errors in parenthesis, WLSMV estimator employed to obtain ordered probit coefficients; *p<0.05;
**p<0.01***p<0.001
Performance
and Place
Layard’s
Predictors
and City
Control
Variables
Combined
Model
Performance
0.287***
(0.038)
0.173***
(0.047)
Place
0.192***
(0.024)
0.172***
(0.037)
Volunteer
0.125***
(0.020)
0.127***
(0.020)
Income
0.113***
(0.020)
0.115***
(0.020)
Health
0.317***
(0.018)
0.323***
(0.019)
Connectedness
0.122***
(0.016)
0.124***
(0.017)
Job
Opportunities
0.063***
(0.016)
0.064***
(0.016)
Trust
0.038*
(0.016)
0.039*
(0.016)
Married
0.117**
(0.036)
0.119**
(0.036)
New York
0.145**
(0.055)
0.148**
(0.056)
Toronto
0.189**
(0.057)
0.192**
(0.059)
Paris
-0.181**
(0.059)
-0.185**
(0.060)
Berlin
-0.101
(0.059)
-0.104
(0.061)
Happiness
Pseudo-R2
0.090
0.172
0.203
RMSEA
0.041
(0.038, 0.045)
0.000
0.071
(0.069, 0.073)
N=
5011
4121
4152
Dear Taylor Bowen and Reviewers,
We are most pleased that you have decided to accept our paper for publication in Urban Design
and Planning, subject to minor changes. We have worked to address reviewer comments.
Specifically, we explain in much more detail our decision to focus upon five cities in our data
set. Please see footnote 5. We also want to understand further why Milan and Stockholm (and
our Asian cities) are somewhat different from the other cities in our data set but felt to do so
was beyond the scope of this particular paper. We plan to investigate this issue in a future
paper. In addition, we now provide two links to our survey questions as requested by Reviewer
#2. Those links are in footnote 3. We have also proofread the paper and corrected typos. We
sincerely hope we have addressed the concerns of this reviewer. Please let us know if additional
clarity is needed.
Please note that we have also added two pictures that we think illustrate attractive urban
places. Once again, thank you for the opportunity to publish our work in Urban Design and
Planning.
With kind regards,
Kevin M. Leyden
PS. I was unable to correct some of the information about me in your system. For example, I
have a Ph.D. and an affiliation with Galway. Here is that missing information:
Kevin M. Leyden, Ph.D. Professor of Political Science, West Virginia University and
Honorary Research Professor of Social Science & Public Policy, National University of
Ireland, Galway
*Response to Reviewer and Editor Comments
... One indicator of happiness that is discussed is the satisfaction and perception that a person has of their environment and how this environment can adversely or positively affect the occupants' mood and behaviour (Hubbard 1992;Goldberg, Leyden, and Scotto 2012). Environmental quality, diversity, attention restoration, legibility, and accessibility are a few theories conjectured between authors as the precursor or path to happiness in an urban environment (Kyatta et al. 2016;Bell 1992;Lawless and Lucas 2011). ...
... Knowledge has emerged from the built-environment industry; however, it remains limited with a relatively broad scope. These papers discuss the association of physical settings with well-being, quality of life, and life satisfaction (Bell 1992;Lawless and Lucas 2011;Goldberg, Leyden, and Scotto 2012). Articles from the field of environmental psychology are also in support of this notion. ...
... Research that has been conducted on the relationship between urban design, happiness, and public health comes from a number of disciplines, not only the built environment. These backgrounds include anthropology, psychology, sociology, epidemiology, geography, economic science, public health fields, landscape planning, and urban planning (Galea et al. 2005;Goldberg, Leyden, and Scotto 2012;Leydon 2005). What is evident from reviewing this literature is that happiness is promoted as being associated and interlinked with access to amenities, leisure facilities, public transport, and more network and location associative functions than the actual physical quality and fabric of the space. ...
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In a world with an increasing urban population, understanding how built environments can facilitate psychological as well as physical well-being is an argument broadly discussed in current literature. “Urban happiness” is a field of research dealing with urban landscapes that foster positive emotions in users and visitors. Understanding the parameters of urban happiness is a complex issue due to different meanings associated with this concept from different social groups. Digital media allows us to gather an understanding of what elements the broader population might associate with happiness in the urban environment through the use of image-sharing platforms such as Instagram. This pilot study was undertaken to identify both built and natural forms that users of a city environment associated with happiness. The thematic analysis of images, which were sourced through Instagram, has allowed identified or emerging themes and features. These have been tested with residents of Brisbane, Australia, through an online questionnaire. The pilot study offers a foundation for further research aiming to understand how people’s self-representation of happiness can be translated in design principles for planners, urban designers, architects, and landscape architects.
... Multiple health outcomes including headaches, arthritis and various respiratory morbidities were also associated to the built environment [7,8]. The perception of the built environment seems to affect HRQoL, defined as "how well a person functions in their life and his or her a1111111111 a1111111111 a1111111111 a1111111111 a1111111111 perceived well-being in physical, mental, and social domains of health" [9]. ...
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Previous research has shown that the built environment plays a crucial role for health-related quality of life (HRQoL) and health care utilization. But, there is limited evidence on the independence of this association from lifestyle and social environment. The objective of this cross-sectional study was to investigate these associations, independent of the social environment, physical activity and body mass index (BMI). We used data from the third follow-up of the Swiss study on Air Pollution and Lung and Heart diseases In Adults (SAPALDIA), a population based cohort with associated biobank. Covariate adjusted multiple quantile and polytomous logistic regressions were performed to test associations of variables describing the perceived built environment with HRQoL and health care utilization. Higher HRQoL and less health care utilization were associated with less reported transportation noise annoyance. Higher HRQoL was also associated with greater satisfaction with the living environment and more perceived access to greenspaces. These results were independent of the social environment (living alone and social engagement) and lifestyle (physical activity level and BMI). This study provides further evidence that the built environment should be designed to integrate living and green spaces but separate living and traffic spaces in order to improve health and wellbeing and potentially save health care costs.
... According to Goldberg, Leyden, & Scotto, (2012) the reason citizens reside in an area is influenced by two dimensions called place and performance [15]. The value of place, in this case, facilitates the ability to enjoy life and attain daily needs. ...
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Disaster is one of the most significant global challenges confronting the society and environment in recent days. It poses a threat to the cultural heritage of conservation areas, including Malay Kampung (Kampung Melayu) Semarang. Today, it is experiencing physical, social and economic degradation, triggered by environmental factors and disasters such as flooding. This research therefore aims to identify the areas of residual disasters and monitor its impact on spatial expression and the resilience patterns. New adaptation and spatial expression develop when there is prolonged contact between flood disaster and the environment. Hence, a spatial expression transformation due to disaster adaptation occurs this expression is a type of resiliency pattern vulnerable in the area. During flood disasters, this pattern is essential to observe and understand the resiliency along with the sustainability of the cultural heritage of these affected areas. This research used qualitative method, Descriptive analysis technique conducted in this study to determining the research area delineation, identifying phenomena of flood disasters in Malay Kampung Semarang, analyzing spatial expression of Malay Kampung Semarang, and determining flood effects on spatial expression. Banjar Kampung was then chosen to represent the entire Semarang Malay Kampung. The spatial expression affected the building conditions, resulting in damage to some inhabited and non-inhabited buildings though some were not severely affected (are in good condition), and however, the buildings can be renovated. Out of the 57 buildings, in the region, 41 are in good condition and 16 others are in damaged condition. The result obtained from the study indicated that the flood phenomenon that occurred is now improved. The occurrence, depth, affected areas and duration of flood has improved as shown in this study.
... Similarly, Goldberg, Leyden, and Scotto (2012) found that the happiness of city residents is linked to their ratings of both place (e.g., ratings of how beautiful they think their city is, how easy it is to gain access to amenities such as parks and movie theatres) and performance (e.g., ratings of the quality of a city's schools, services for the disadvantaged, safety) variables, which have both direct and indirect effects on citizens' happiness through social connection and health. Building on this research, Hogan and colleagues (2016) examined how the importance of these variables varies across the lifespan. ...
Chapter
Western culture has developed an obsession with happiness. At first glance, the premium placed on happiness seems warranted given that a large body of research has highlighted its benefits. Yet, emerging lines of research suggest that the outcomes of being happy are very different from the outcomes of seeking to be happy. Whereas the former is often linked to, and in some cases even causes, positive outcomes, the latter seems to do the opposite. This chapter first reviews research examining the negative effects of pursuing happiness at the individual level. We then highlight a number of important differences between Western and Eastern notions of happiness while also considering how these notions are beginning to change. Next, we examine the consequences stemming from valuing happiness at the societal level. We discuss prominent cultural emotion norms tied to happiness and the implications that these norms have for individual emotional functioning. Throughout, we note that the downsides of pursuing happiness may spread to other Eastern societies, such as the Middle East/North Africa region, through increased exposure to Western values, norms, and practices via globalization. Lastly, we highlight a number of important social determinants of happiness that can inform governments in their mandate to boost the happiness, life satisfaction, and overall wellbeing of their citizens.
... In this study, we extend the above line of research by exploring the previously untapped source of employee well-being, which is hotel design aesthetics. Human wellbeing has been conceptually and empirically linked to aesthetics (Andrews & Withey, 2012;Goldberg, Leyden, & Scotto, 2012;Hamermesh & Abrevaya, 2013;Sirgy, Efraty, Siegel, & Lee, 2001). Longing for or the expression of beauty are believed to be a basic human need to continue towards self-actualization (Maslow, 1970). ...
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The study recognizes the lack of a clear theoretical and empirical link between employees' sense of well-being and hotel design aesthetics, although beautiful environments are associated with optimal human functioning. Drawing on conceptual insights from organizational aesthetics and theory of subjective well-being, this quantitative study explored relationships between workplace design aesthetics, hotel employee subjective well-being and the role of contrast of back-vs. front-of-the-house. Based on cross-sectional data collected from 525 operations-level hotel employees in USA, the study found that backstage employees experience less aesthetic pleasure and report lower levels of well-being than frontstage employees. Design characteristics Unity and Variety positively affect the sense of well-being, while Typicality exhibits a U-type relationship with well-being. The effect of Variety is weaker for back-of-the-house employees. This study is the first attempt to empirically and explicitly connect organizational aesthetics to well-being and identifies a novel way to enhance the well-being of the hospitality workforce.
... Sedangkan contentment merupakan komponen kognitif yang mencerminkan tingkatan di mana yang didapatkan oleh individu bertemu dengan aspirasinya. Menurut Layard (2005) dalam (Goldberg, Leyden, & Scotto, 2012), terdapat beberapa faktor yang mempengaruhi kebahagiaan seseorang, yaitu pendapatan atau kondisi finansial, hubungan keluarga, persepsi terhadap pekerjaan, hubungan sosial terhadap komunitas, dan kesehatan. ...
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The measurement of happiness index in Indonesia was conducted by Badan Pusat Statistik (BPS) was first released in 2013 based on the result of study and representation of national level estimation. The approach taken is a life satisfaction, in which life satisfaction is believed to reflect the level of happiness. The city of Bandung is one of the cities that initiated the measurement of happiness index in Indonesia. Kampung Braga is one of Kampung Kota that still maintain its existence in the middle of the urban development. The neighborhood of Kampung Braga is considered as slum area and the buildings within break the river border line. According to than phenomena, the research question comes up, "How big is the level of happiness Kampung Braga neighborhood?". Variables used ini this research consist of happiness and spatial variables. The analysis used is descriptive quantitative by weighting and scoring on each variable. Based on the results, the happiness index of Kampung Braga neighborhood is 0.978 which belongs to the category of very happy. In forming proccess of happiness, the affective component contribution is relatively balanced with the cognitive. Spatially, people in RW 04 and RW 08 tend to be happier. This study proves that the people of Kampung Braga have the ability to adapt to the urban environment.
Thesis
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With high levels of inequality, poverty and high crime rates, South Africa tends to rank relatively low on the quality of life indexes, i.e. South Africa forms part of the bottom 10 countries on the Happy Planet Index. In view of this, spatial decision-makers are often criticised to have failed in delivering meaningful improvements in settlements with an urgent need for an improved quality of life. Urban areas are, however, quite complex and the various role-players within this system have different and often conflicting, views and visions towards a “good and happy” human settlement. These conflicting rationalities are regarded as one of the key obstacles in overcoming the life quality challenges in South Africa. Considering these life quality challenges in South Africa and the substantial influence that the spatial organisation of urban areas has on life quality, it is argued that finding solutions to these life quality problems are, in part, the responsibility of the spatial planner. Subsequently, this thesis explored conflicting quality of life rationalities between spatial decision-makers and the South African poor. The research followed a grounded theory research approach to ground the analysis in data without preconceived ideas. Qualitative storyline and case study analyses followed a preliminary literature review to avoid repetition and to enhance sensitivity to nuances in the data. The storyline analysis considered the underlining quality of life rationality in South African directives guiding spatial decision-making, along with that in four Quality of Life Index reports. The case study analysis explored the quality of life rationality in 8 low-income settlements, namely Alabama, eMbalenhle, Freedom Park, Kanana, KwaDela, Lebohang Matlwangtlwang and Zamdela. Secondary data of semi-structured interviews regarding broad quality of life topics were utilised for this case study analysis. The data for both analyses were respectively reduced by a process of coding on ATLAS.ti, a computer-aided qualitative data analysis software. The coding set revealed the broad categories of the quality of life and the quality of life rationalities were reflected upon according to these categories. To consider conflicting quality of life rationalities, the findings of the two analyses were juxtaposed. The research concluded that the conflicting rationality between spatial decision-makers and the South African poor mainly stem from the diversity of the South African context. Subsequently, this research contributed a conceptual framework towards avoiding conflicting quality of life rationalities during strategic spatial planning and recommended spatial strategies to address life quality challenges and scope for future research.
Article
As the urban world population grows steadily, cities have become the main habitat for human beings. Against this backdrop, city quality or the level of development of the city's habitat that ensures the satisfaction of objective and subjective human needs become a matter of growing interest and concern for academics, policy makers, and citizens. Building on a resource‐based view of city quality, the aim of this paper is twofold. First, it proposes and validates scales for six city sub‐habitats: political, economic, social, natural, artificial, and technological. Second, it tests a model and the underlying hypothesis about the ranking of those sub‐habitats and of the perceived controversy regarding decision making upon them. For those purposes, a survey of 768 city inhabitants was conducted in Portugal to measure city quality and their sub‐habitats. Both the predicted ranking of importance of the sub‐habitats and the perceived ranking of controversy were empirically validated. The results constitute a novel and important contribution to understand city quality and its sub‐habitats, whose conceptual power relies on hierarchized factors linked to citizens’ happiness and to the level of controversy of the solutions.
Article
Purpose Cities from developing countries strive to compete on a global scale and hence try to attract and retain their residents in offering higher liveability. This study examines the extent to which liveability influences resident’s sense of place and determines residents’ behavioural intentions. Design/methodology/approach A survey was carried out to test the hypotheses using a sample of 362 residents from the city of Dubai (UAE). Structural equation modelling and the method suggested by Hayes and Preacher (2010) for mediation analysis were used. Findings Findings show that residents’ preferences for different types of liveability attributes (included in seven dimensions) influence their sense of place that in return shape their behavioural intentions toward their place of residence. Results also reveal the importance of non-economic attributes of the urban environment. Moreover, residents’ sense of place mediates the relationship between liveability and residents’ behavioural intentions. Research limitations/implications Future research could more deeply investigate the social functioning of a place and particularly the role of place identity as it is recognized to affect residents’ attitudes and behaviours. In addition, further developments may contribute to the ongoing debate on the relationship between liveability and growth. Practical implications From a public policy standpoint, this study suggests that local authorities need to identify a distinct set of economic and non-economic characteristics that will encourage residents to stay longer in the place they live. As such, enhancing liveability represents a critical strategic initiative for cities from developing countries in order to make them a great place to live. Originality/value Compared to developed countries’ cities, few attempts have been made to investigate the attitudes of residents towards a place and the role of liveability in the context of emerging countries fast-growing urban areas. In addition, findings revealed the importance of place-based meanings, i.e. sense of place, which played a pivotal role in the development of place-protective behaviours.
Book
'Whether you're looking for economic realities expressed through mathematical formulae, classical history, Immanuel Kant's ethics, or sustainable development, there's something here for you. . . I suggest that you read it.' © Luigino Bruni and Pier Luigi Porta 2007. All rights reserved.
Book
How much do we know about what makes people thrive and societies flourish? While a vast body of research has been dedicated to understanding problems and disorders, we know remarkably little about the positive aspects of life, the things that make life worth living. This volume heralds the emergence of a new field of science that endeavours to understand how individuals and societies thrive and flourish, and how this new knowledge can be applied to foster happiness, health and fulfillment, and institutions that encourage the development of these qualities. Taking a dynamic, cross-disciplinary approach, it sets out to explore the most promising routes to well-being, derived from the latest research in psychology, neuroscience, social science, economics, and the effects of our natural environment. The book provides an overview of the latest insights and strategies for enhancing our individual well-being, or the well-being of the communities in which we live and work.
Book
Do places make a difference to people's health and well-being? This book demonstrates how the physical and social characteristics of a neighborhood can shape the health of its residents. Researchers have long suspected that where one lives makes a difference to health in addition to who one is. Almost everyone understands that smoking, unhealthy eating, lack of exercise can compromise longevity and good health, but can a person's ability to maintain a healthy lifestyle be affected by the smoking habits of other people close by, or access to grocery stores, or the existence of safe parks and recreational space? The answers to this question and other similar ones require new ways of thinking about the determinants of health as well as new analytical methods to test these ideas. This book brings together these ideas and new methods. The book contains various parts. The first part deals with methodological complexities of undertaking neighborhood research. The second part showcases the empirical evidence linking neighborhood conditions to health outcomes. The last part tackles some of the major cross-cutting themes in contemporary neighborhood research.
Technical Report
Available online at: https://population.un.org/wup/Download/