Urban Environment and Mortality Differentials in Southern Spain
Francisco Viciana, Junta de Andalucia
Diego Ramiro-FariƱas, Spanish National Research Counsel (CSIC)
Mathias Voigt, EU ITN Marie CurieLongpop project
Dariya Ordanovic, ESRI Spain
Rosa Canovas, Institute for Cartography and Statistics Andalusia
Background and Objective
According to the latest United Nationsprojection about two thirds of the world population will live in areas
classified as urban by the year 2050 [1].While accelerating growth of cities in terms of area and population
size will trigger broad changes insocial structure or occupational activities it also bears substantialchallenges
regarding social equity and thesustainability of public health systems [2, 3].Comparative analyses in rapidly
urbanizing countries suggest thateffects of crowding, pollution and the simultaneous adaption of unfavorable
life styles can lead to an increasedprevalence of diseases and health problems among the urban population
[4].
Although recently contested [5],also historical public health research often understands cities as high-risk
environments associated to the vastspread of infectious diseases and crime [6, 7].Hence, the urban penalty
hypothesis gained popularity in publichealth research, even though it was coined to describe vastly urbanizing
areas during the industrialization [8].In spite of the reduction of mortality through remarkable public health
interventions since the beginning ofthe century, there is consensus that the exposure of urban environment
affects health and wellbeing throughair and noise pollution [9, 10].
While analyzing direct effects ofpollution and access to green spaces on specific health outcomes i1s presumably
intuitive, the examinations of overallhealth in response to the exposure to an urban environment requires
linkable multi-level data and skillfulhandling of latent concepts. The absence of a universal definition of what
is rural and urban has often led tosimplifications in the analysis strategy, most commonly the lack of other
urban features than population density[11]. Furthermore, the examination of complex association between
health and residential environmentrequires access to rare linkable individual level information. With the help
of our project partner, the Instituteof Cartography and Statistics of Andalusia (ICEA), we aim to overcome
the aforementioned limitations. Theirlongitudinal individual level mortality data base allows a linkage to a
register-based residential informationand enables us to conduct a detailed analysis of mortality differentials
by environmental small area featuresfor Andalusia, the southernmost and most populated of the 17 Spanish
autonomous communities.
Data and Analysis Strategies
Following Vhalov and Galea (2002) [12],we generate a multidimensional indicator for our latent variable
urbanicity, whichrelates to the degree of urban characteristics including population density andartificial surface
area on census tract level. Theconcentration of urban areas in Andalusia is depicted in figure 1 by apreliminary
indicator. Through our project partnerwe are able to link the environmental information to the population and
housing census of 2001 and a 10 %mortality follow-up of the census population of Andalusia. The combination
of these information allow us to examinehow residential environment features affect individual level mortality
over a time period of 13 years.Considering the multilevel structure of our data, we aim to apply an adaptedCox
proportional hazards model with mixedeffects. To account for possible clustering in the baseline hazard, the
classic model is extended bystratum-specific term Wi = log !i whichcan be incorporated as in the following
equation.
h(ti;j ; xi;j) = h0(ti;j) exp(_T xi;j +Wi) (1)
where h0 isthe baseline hazard with multiplicative effects by the exponential terminvolving the covariates
and the Wi,the normally distributed stratum specific frailty term designed to capture thedifferences between
Preliminary results and Outlook
The preliminary results of our survival analysisindicate the existence of a small but highly significant urban
mortality penalty in modern day Andalusia. Thehazard ratios and goodness of fit parameters of two classic Cox
proportional hazard models are displayed in table1. To measure the impact of urbanicity, we use a preliminary
indicator and do not apply the aforementionedgeographical measures yet. Whereas urban environment
features do not seem to affect the risk of dyingin a model without further covariates, their effect sizes increase
and are strongly significant for the full modelcontaining socioeconomic and demographic control variables
(model 2 - shortened). The preliminary resultsindicate the existence of a mortality disadvantage for urban
dwellers in modern-day Andalusia.
In following steps, we aim to apply theaforementioned extension of the Cox model which allows for the
incorporation of spatial position of small areasand supports the detection of clustering and neighboring
effects. Furthermore, we plan to generate acomparative measure for urbanicity and control for theadditional
socio-spatial context variables which potentiallymitigate the effect of area deprivation on the urban health
penalty. If possible, we will also join theindividual information on household level.
Presented in Session 1235: Environment, Development, and Space