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Masood Gheasi, Noriko Ishikawa, Peter Nijkamp , Karima Kourtit
ABC Contribution: The City of Health
• Human Health and the Urban-Rural Dichotomy: An Overview
•A meta-analysis of health effects of urban and rural living patterns
Urbanization and quality of Life
Paper overviewThe health outcomes are well known to be affected by not only
individual socioeconomic status, but also by the physical environment, and socioeconomic and political circumstances including “urbanization”.
This paper aims to offer an inventory of studies that have addressed the relationship between urban conditions and human health and to examine why the estimated effects of urbanization vary among countries or studies.
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Urbanization and quality of Life
The definition of urbanityThe definition of urbanization varies across countries and during
different periods reflecting their geographical and socio-economic differences.
Some studies follow a classification scheme from the National Census (e.g., UIC or RUCC in the U.S., ONS or ACORN in England).
Criteria of urban areas is often determined by population size, density or whether people are living in a core city or not.
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Urbanization and quality of Life
Step1: InventoryUrban/rural effects on health outcomesOverview of several papers addressing health inequality between
urban and rural areas…(99 papers)
29 papers: advantage of urban living for health
42 papers: advantage of rural living for health
13 papers: different results depending on health outcomes
5 papers: no significant differences in health outcomes between urban/rural living
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Urbanization and quality of Life
6 contextual effects on health outcomes (1)
Housing conditions (direct/ indirect)Access to safe water and adequate sanitation facilitiesStructural housing characteristics (housing type, floor level, quality)Housing tenure (proxy of residential stability or spatial deprivation)
Environmental hazardsThe exposure to air pollution (whether living near a major road,
highway, or noxious facilities)
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Urbanization and quality of Life
6 contextual effects on health outcomes (2)
Land use mix and spatial segregationProximity to facilities (amenities, retail services, work place)Degree of urban sprawl (mixed land use, neighbourhood diversity,
population density, automobile dependency, proximity to metropolitan area)The degree of walkability (residential density, street connectivity, extent of
mixed land use, retail floor area ratio)The degree of social/racial segregation
Residential proximity to CBDCommuting distance, time (proximity to metropolitan area)Intra-area relationship (spatial autocorrelation)Degree of spatial (geographical)/socioeconomic isolation
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Urbanization and quality of Life
6 contextual effects on health outcomes (3)
Accessibility to and availability of medical services(Accessibility)Time and distance from home to health care facilities(Availability)The number of physicians (GPs/specialists), health care facilities, and some
related facilities (acute/chronic services, medical/nursing care services)
Population densityA proxy of living conditions (narrow houses, a lack of open/green spaces,
traffic congestion, high exposure to pollution, lower transportation costs, accessibility to services and amenities, neighbourhood walkability, employment opportunities, and human capital accumulation)
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Urbanization and quality of Life
Inconsistency in the urban/rural effects
A series of studies have described the defects in urban/rural dichotomy (Higgs, 1999; McDade and Adair, 2001, Vlahov and Galea, 2002; Hall et al. 2006; Laditka et al., 2007; Berke et al., 2009; Peen et al., 2010)
Inconsistency in findings may come from (1) a not-unified (inappropriate) classification scheme, and (2) an intra-regional heterogeneity.
It is important to find a classification scheme that minimizes the heterogeneity within regions.
Inconsistency in the results from different studies appears to be due the ambiguous definition of urbanity and an intra-regional heterogeneity (e.g., inner-city areas).
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Urbanization and quality of Life
Various measures of heath statusSubjective health statusSRH (self-rated health) scores
LLTI (limiting long-term illness)
Objective health statusICD (International Classification Diseases)
GHQ (General Health Questionnaire)
mortality rate/life expectancy
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Urbanization and quality of Life
Step 2: Meta AnalysisStudy Characteristics We included research papers that take first ‘self-rated’ or ‘self-
reported’ physical health and secondly include ‘urban’, ‘rural’, ‘city residence’ differences since 1999 into account.
12 studies that yielded altogether 221 point estimations.
In this study, we focus on good-excellent physical health.
Unadjusted vs adjusted estimations
Journal impact factor as an identification factor for the quality
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Urbanization and quality of Life
The numerical attributes include the calculated standard error, OR for urban, semi-urban, semi-rural and rural, number of observation per regression, and t-values.
The study characteristics are coded as dummy variables, and equals 1 in each regression that includes that particular attribute, 0 otherwise.
The decision to code characteristics of each study is not an easy taskwe coded the habits such as smoking, and alcohol consumption as
one variable called “addiction” social trust, social support and social capital under another dummy
variable, called “social”. 11
Urbanization and quality of Life
Study Time period
Country # estimation
Mean
Gerdtham and Johannesson (1999)
1991-1991 Sweden 4 0.968
Hyyppä and Mäki (2001) - Finland 6 1.35
Leinsalu (2002) 1996-1997 Estonia 4 1.19
Auchincloss and Hadden (2002)
1989-1991 US 54 0.866
Kim and Kawachi (2006) - US 24 0.956
Maas et al. (2006) - NL 24 0.991
Riva et al. (2009) 2000-2003 UK 13 0.865
Sharkey et al. (2011) 2006-2006 US 2 1.505
Monnat and Pickett (2011)
2002-2008 US 16 1.113
Bthea et al. (2012) 2006-2006 US 6 1.03
Lankila et al. (2012) 1997-1997 Finland 48 1.317
Haraldsdóttir et al. (2014)
2007-2007 Iceland 8 1.39
Study Characteristics (1)
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Urbanization and quality of Life
Study Characteristics (2)
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Negative and
statistically significant
Negative and
statistically not
significant
Positive and statistically
not significant
Positive and statistically significant
Total
Urban 30% (29) 33 % (19) 19 % (11) 18 % (10)100% (57)
Semi-urban 13 % (7) 48% (25) 12% (6) 27% (14)100% (52)
Semi-rural 23% (9) 46% (18) 21% (8) 10% (4)100% (39)
Rural 22% (19) 32% (13) 3% (18) 17% (10)100% (60)
Urbanization and quality of Life
Study Characteristics (4)
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Urbanization and quality of Life
Meta-regression model
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We aim to investigate to what extent the variation in health outcomes between and within studies can be related to the study characteristics.
If we assume that the true effect size varies from one study to the other, a random effect meta-regression model is applicable (we apply the algorithm of restricted maximum likelihood with the Knapp-Hartung modification, see Harbord and Higgings, 2000).
If we assume that there is no variation between the studies, then we use the FE meta-regression. weighted least square (WLS) with the weights of variables equal1/(𝛼𝑖𝑗). The standard errors of the regression are to be adjusted with the cluster of
observations defined by 12 studies.
Urbanization and quality of Life
Key findings (I)
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(1) (2) (3)
VARIABLES OLS FE RE
standard error 1.129 (0.228)*** 0.259 (0.478)
urban -0.0154 (0.0331) -0.0111 (0.0356) -0.0597 (0.0268)**
semi-urban 0.0962(0.0319)*** 0.0386 (0.0345) 0.0616 (0.0280)**
semi-rural -0.0349 (0.0343) -0.0226 (0.0356) -0.0241 (0.0330)
before 2000 -0.274 (0.0674)*** -0.354 (0.0987)*** -0.316 (0.0784)***
female 0.0621(0.0369)* 0.0762(0.0343)** 0.0539(0.0416)
adjusted -0.125 (0.0511)** -0.125 (0.0575)** -0.144 (0.0436)***
journal impact factor -0.120 (0.100) -0.340 (0.187)* -0.269 (0.102)***
Urbanization and quality of Life
Key findings (II)
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(1) (2) (3)
VARIABLES OLS FE RE
family income 0.154(0.104) 0.112 (0.0491)** 0.146 (0.0836)*
education -0.0800 (0.0786) -0.0880 (0.0816) -0.0809 (0.0792)
employment -0.0624(0.0909) -0.0822(0.0510) -0.0792(0.0799)
length of residence -0.0979 (0.0807) -0.0709 (0.0775) -0.0790 (0.0818)
material condition 0.0842 (0.157) 0.529 (0.186)*** 0.299 (0.147)**percentage of green place 0.127 (0.0770) 0.116 (0.0541)** 0.138 (0.0585)**
religious -0.0505(0.0953) -0.0188(0.141) -0.0374(0.0745)
physical activity 0.0509(0.0807) 0.0644(0.0722) 0.0710(0.0845)
Urbanization and quality of Life 18
(1) (2) (3)
ordinal 0.451(0.110)*** 0.576(0.158)*** 0.577(0.101)***
multilogit -0.0245(0.0399) -0.0455(0.0434) -0.0220(0.0367)
race 0.162(0.0735)** 0.130(0.0786) 0.147(0.0615)**
community predictor -0.140(0.0896) -0.308(0.0961)*** -0.223(0.0767)***
occupation 0.0494(0.128) 0.479(0.245)* 0.262(0.130)**
migratory behavior 0.592(0.290)** 0.921(0.389)** 1.061(0.266)***Health personal shortages -0.160(0.111) 0.0591(0.101) -0.0779(0.0907)
loneliness feeling -0.149(0.0807)* -0.122(0.0991) -0.160(0.0853)*
constant 1.071(0.0118)*** 1.071(0.0144)*** 1.063(0.0118)***
Observations 209 209 209
R-squared 0.733 0.684
Urbanization and quality of Life
ConclusionA meta-analysis approach is one of the effective methods for
estimating the effect size across countries/studies.
There is also ambiguity regarding the direction of the relationship.
Further research on direction and statistical significance of empirical estimated of self-rated/reported health.
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