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Journal of Environmental Psychology 32 (2012) 305e317

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Journal of Environmental Psychology

journal homepage: www.elsevier .com/locate/ jep

Multiple environmental burdens and neighborhood-related health of cityresidents

Jasmin Honold a,*, Reinhard Beyer a, Tobia Lakes b, Elke van der Meer a

aDepartment of Psychology, Cognitive Psychology, Humboldt-Universität zu Berlin, Rudower Chaussee 18, 12489 Berlin, GermanybDepartment of Geography, Geomatics, Humboldt-Universität zu Berlin, Rudower Chaussee 16, 12489 Berlin, Germany

a r t i c l e i n f o

Article history:Available online 23 May 2012

Keywords:Environmental stressUrban greenWell-beingNeighborhood satisfactionGeographic information systemsSustainable urban development

* Corresponding author. Tel.: þ49 30 2093 9398; faE-mail addresses: jasmin.honold@hu-berlin.de (

psychologie.hu-berlin.de (R. Beyer), tobia.lakes@gvdMeer@rz.hu-berlin.de (E. van der Meer).

1 Thus, in this article the term neighborhood-relaonly symptoms of poor mental and physical health,faction and life satisfaction as indicators of well-bconcept of well-being, see Kiefer (2008) and New2008).

0272-4944/$ e see front matter � 2012 Elsevier Ltd.doi:10.1016/j.jenvp.2012.05.002

a b s t r a c t

Urban living environments are known to influence human well-being and health; however, little isknown about the multidimensionality of different environmental burdens. The aim of this study is toexamine the relations between multiple burdens and self-rated health of city residents in Berlin. A spatialanalysis was conducted to determine neighborhood street blocks with high versus low levels of threeenvironmental burdens (traffic noise, air pollution, lack of public green space) as study sites for a cross-sectional household questionnaire. Burden level served as a dichotomous predictor to compare residents’self-reports of neighborhood satisfaction, life satisfaction, health behavior, and psychological andphysical health symptoms. Residents from high-burden blocks appraised the environmental conditionsmore stressful, reported poorer health behavior and were less satisfied with their neighborhood thanresidents from low-burden blocks. However, they did not differ in regard to more general healthsymptoms. Three other burdens (behavior-related noise, litter and dirt in public space, lack of urbanvegetation), which could not be varied objectively, were assessed by their perceived intensity. Regressionanalyses of the relations between the perceived levels of all six burdens and outcomes in the total samplerevealed the following: Neighborhood satisfaction could be predicted from multiple stressors andresources that co-occur independently, while more general health symptoms were related only toperceived air pollution. The results have implications for both urban planning and public health.

� 2012 Elsevier Ltd. All rights reserved.

1. Introduction

In the light of rapid world-wide urbanization processes, currentpublic debate and research in multiple disciplines focuses on howto design, develop and manage cities sustainably so as to providecity dwellers with health-supportive habitats. According to theWorld Health Organization’s definition of health (World HealthOrganization, 1946), urban neighborhoods must ensure not onlythe absence of disease or infirmity, but also support a state ofcomplete physical, mental and social well-being.1 Improvinghabitats within dense urban areas implies the use and increase ofbenefits from ecosystem services, as well as the reduction of

x: þ49 30 2093 9361.J. Honold), reinhard.beyer@eo.hu-berlin.de (T. Lakes),

ted health encompasses notbut also neighborhood satis-eing. For discussions of theEconomics Foundation (NEF,

All rights reserved.

pollution and environmental burdens (Bolund & Hunhammar,1999; Endlicher et al., 2011). To date, the dominant researchapproaches have focused on health effects of singular environ-mental resources (i.e., potentially beneficial factors) or burdens (i.e.,potentially harmful factors) and/or on singular levels of inquiry(e.g., individual, neighborhood, community). However, the demandfor comprehensive research integrating multiple factors andmultiple-level approaches to better understand the complexities ofenvironmental factors has recently increased (cf. Galea,Freudenberg, & Vlahov, 2005). Consequently, the present paperaims at an integrative understanding of the relations betweenurban environmental stressors and resources, and neighborhood-related health. After presenting the existing theoreticalapproaches and empirical results from both research perspectives(environmental stress and environmental resources), we developan integrative framework that we apply to our empirical study.

1.1. Environmental stress and neighborhood-related health

Many of today’s urban environmental burdens that influencehuman health can be subsumed by the concept of ambient

J. Honold et al. / Journal of Environmental Psychology 32 (2012) 305e317306

stressors. Ambient stressors are defined as environmental factorsthat are perceptible (although they may go unnoticed), chronicallypresent, negatively valued, non-urgent and intractable, meaning anindividual cannot alter these stressors structurally (Campbell,1983). They might impact behavior and health not only by phys-ical, but also subjective means in that they elicit stress reactionsthrough different, context-dependent cognitive and emotionalpathways that are illustrated in an eclectic model from Bell, Greene,Fisher, and Baum (2001). Following this model, environmentalstimuli are perceived and appraised in regard to personal adequacyof stimulation. These processese appraisal more than perceptione

are influenced by physical properties of the stimuli, as well aspersonal attributes and situational conditions. Homeostasis issustained if stimuli are within the desired range of stimulation,which may contribute to positive affect, neighborhood satisfactionand thus, to life satisfaction (Amérigo, 2002; Francescato, 2002).However, individuals appraise environmental factors negativelywhen they perceive a shift from homeostasis toward disinclination(cf. Klix, 1983). Lazarus and colleagues have extensively describedand studied this process as stress appraisal (Lazarus,1991; Lazarus &Cohen, 1978; Lazarus & Folkman, 1984; Lazarus & Launier, 1978).Negative appraisal may result in heightened arousal, changes inemotional states, in cognitive functions and behavior. Subse-quently, a coping strategy (i.e., an intentional behavioral or intra-psychic effort) is chosen to restore homeostasis and accordingly,the stimulus is reappraised. If coping was successful, the samestimulus is less likely to cause negative appraisal and/or the cor-responding reactions the next time it is perceived. Otherwise,heightened arousal continues or stress is even intensified due tounsuccessful coping efforts. Prolonged or repeated exposure tostressors can enhance the risk of detrimental after-effects such asmood disturbances, social withdrawal, sleep loss or elevated bloodpressure (Adler & Hillhouse, 1996; Cohen, Evans, Stokols, & Krantz,1986; Dougall & Baum, 2001; Marsland, Bachen, Cohen, & Manuck,2001). While the eclectic model is capable of explaining inter-individual differences in reaction to an acute environmental stim-ulus, it needs to be specified for field research on long-term effectsof neighborhood burdens in three aspects: the concept of coping,physiological pathways, and the co-occurrence of multiple burdens.

First, coping strategies successful in mitigating stress reactionsare likely to be maintained. While this is a well-adaptive mecha-nism in most cases, one stress-attenuating strategy deservesspecial interest because it poses a health risk on its own:Consumption of psychotropic substances such as alcohol andnicotine. For example, smoking was shown to increase withelevated levels of ambient stress (Cherek, 1985). Conversely,unsuccessful coping efforts are unlikely to be sustained overa longer period of time and may be displaced by passive mindsets(e.g., prolonged concern or resignation; Homburg & Stolberg, 2004;Ruff, 1990). Moreover, two other intrapsychic assimilation mecha-nisms occurring on a rather unconscious level are plausible withrepeated or prolonged exposure to environmental burdens:Cellular adaptation occurs when neurophysiological sensitivitydiminishes, resulting in modified perception (cf. Campbell, 1983).Cognitive habituation may occur because stimulus uncertainty isreduced or due to reduction of cognitive dissonance and results inmodified appraisal (Festinger, 1957). In short, negative appraisal ofpermanent environmental conditions and frequent substanceconsumption can be regarded as a result of the inability toconstructively cope with, adapt to or habituate to environmentalburdens. Both phenomena are a health risk factor and thus, ofcentral interest.

The second aspect in Bell et al.’s (2001) model to be explicatedrefers to the finding that subjective stress responses do not alwayspredict the elevation of physiological responses (Kirschbaum,

Kudielka, Gaab, Schommer, & Hellhammer, 1999). Thus, environ-ments with high ambient stressor levels may permanently elicitneural and neuroendocrine responses, regardless of cognitiveprocesses. When this state of ‘allostatic load’ (McEwen, 2000)coincides with other risk factors such as higher age, low socialstatus or low social support (Picket & Pearl, 2001; Wills & Fegan,2001), the risk of stress-related symptoms enhances (e.g.,retarded speed of disease recovery, susceptibility to infectiousdiseases, hypertension, steroid diabetes, ulcers, etc.; for reviews,see Carlson, 2004; Dougall & Baum, 2001; Kaltsas & Chrousos,2007; Marsland et al., 2001).

Finally, the model focuses on how singular stressors act.However, neighborhoods may be confronted with multipleambient stressors that are present at the same time, as they mightco-vary in spatial and temporal occurrence when emitted from thesame source (e.g., road traffic emits noise, unpleasant odors, and airpollutants at the same time). According to Lepore and Evans (1996),multiple environmental stressors exert independent effects whenone stressor does not deplete general coping resources, when itdemands a different reservoir of resources (e.g., social vs. materialresources), or different strategies (e.g., mental problem solving vs.passive acceptance) than other stressors. Thus, a potentiating effectis more likely when acute stress elicited by one factor reducescapacity to cope with or adapt to concurrent or subsequentstressors.

In the literature on ambient stressors, traffic noise has receivedmore attention than other omnipresent forms of environmentalpollution (e.g., unpleasant odor burdens, litter, heat waves, airpollution, noise from other sources such as industry or humans; forreviews see Bullinger, 1998; Cohen et al., 1986; Craik & Zube, 1976;Evans, 2001, 2003; Glass & Singer, 1972; Moser & Robin, 2006;Taylor, Repetti, & Seeman, 1997). While short-term stress reactionsto acute ambient stressor exposure and negative appraisal reac-tions to long-term exposure are well accepted for most of thesefactors, clear evidence of long-term health effects is lacking. Clarkand Stansfeld conclude in their review (2007) that traffic noiseimpacts subjective quality of life, increases psychological symp-toms reporting, and is marginally associated with an enhanced riskof hypertension and coronary heart disease. Conversely, air pollu-tion seems to have a small but significant relation with clinicallydiagnosable mental health outcomes (see Evans, 2003).

In regard to the effects of multiple stressor exposure, interac-tive effects of one ambient stressor with another kind of stressor(e.g., stressful life events, work and personal project stress, etc.)cannot be excluded (Evans, 2003;Wallenius, 2004; for reviews, seealso Gump & Matthews, 1999; Lepore & Evans, 1996). However,there are few publications on how multiple ambient stressors co-occur. In experimental studies, an interactive effect was found fornoise and social crowding, but not for noise and vibration(Ljungberg & Neely, 2007; Martimportugués-Goyenechea &Gómez-Jacinto, 2005). In neighborhood research, physicalambient and social stressors (e.g., loitering, incivility, neighbor-hood maintenance or structural problems, signs of crime, etc.) areoften aggregated into one single stress indicator (Agyemang et al.,2007; Dalgard & Tambs, 1997; Ellaway, Macintyre, & Kearns, 2001;Feldman & Steptoe, 2004; Matheson et al., 2006; Silver, Mulvey, &Swanson, 2002; Weich et al., 2001). According to these studies,neighborhoods with higher stress scores tend to be of lowersocioeconomic status than areas with lower stress scores. More-over, their residents tend to report lower neighborhood satisfac-tion and poorer physical and mental health, controlling forindividual-level socioeconomic status. These studies implicitlyassume additive stressor effects, but the relative contributions ofsingle stressors to overall effects and their interplays remainunrevealed (see also Winkel, Saegert, & Evans, 2009).

J. Honold et al. / Journal of Environmental Psychology 32 (2012) 305e317 307

1.2. Environmental resources and neighborhood-related health

In addition to the impact of urban environmental stressors onhuman health, the beneficial effects of urban ecosystems haverecently received growing interest (e.g., Ward Thompson, Aspinall,& Bell, 2010). There are two main research positions that argue forevolutionary-based benefits of natural environments, a psycho-physiological approach and a cognitive mechanisms approach. Inshort, the first tradition arose from Ulrich’s stress reduction theory(SRT) and focuses on the capacity of natural environments to fosterrestoration, that is, recovery from environmentally and otherwiseinduced stress (Ulrich, 1983). According to SRT, natural environ-ments provide restoration by visual characteristics that signalresources relevant to survival and well-being. Due to an inheritedtendency of humans to respond to such cues with positive affect,these environments aid return to moderate levels of autonomicarousal (see also Orians & Heerwagen, 1992). The other tradition isbased on Kaplan and Kaplan’s attention restoration theory (ART,1989). ART assumes natural environments enable recovery fromdirected attention. This capacity is explained by specific qualitiesinherent in natural environments that allow for effortless attention.Kaplan (1995) suggests an integration of these two perspectives.Specifically, as stress reduction might enhance attention capacity,restored attention might contribute to stress reduction, or positiveeffects of natural environments on both functions could be plau-sible. Beyond these pathways, urban green spaces may supporthealth in additional, indirect ways (cf. De Vries, 2010). That is, theymight stimulate physical activity, which is in turn beneficial tohealth (see Phillips, Kiernan, & King, 2001, for a review). Moreover,theymight enable or facilitate social contacts and thus help gainingsocial support, which protects against poor health, as discussed inSection 1.1.

Numerous studieshave showngreaterbeneficial effects ofnaturalvs. non-natural environments. Public green spaces in close proximityto home buffer the impacts of stressful life events (Van den Berg,Maas, Verheij, & Groenewegen, 2010; Wells & Evans, 2003). Theyare related to enhanced neighborhood satisfaction, self-reportedphysical health and longevity, and to reduced anxiety and depres-sion (Maas, Verheij, Groenewegen, deVries, & Spreeuwenberg, 2006;

Neighborhood Level

Lack ofResources

MultipleStressors

Individual Level

Stressor 1

Stressor 2

...

StressAppraisaPerception

Perception

Personal &Situational Factors

Resource 1

Resource 2

Fig. 1. Framework of the present study on multiple co-occurring neighborhood-level burdenindicators. Potential interactions among multiple burdens are investigated in an explorator

Maas et al., 2009; Takano, Nakamura, & Watanabe, 2002). Whileresearch has mainly focused on the use of green spaces, thefrequency of visiting these areas does not fully explain such effects(Nielsen&Hansen, 2007). Someauthors suggest that visual exposureto shared natural space or vegetation in general might explain thehealth effects of these resources (e.g., Aries, Veitch, & Newsham,2010; Hur, Nasar, & Chun, 2010; Kaplan, 2001; Kearney, 2006; Kuo& Sullivan, 2001). Moreover, small patches of green and vegetationmay stimulate the use of outdoor spaces and social activities(Sullivan, Kuo, & Depooter, 2004).

1.3. Integrative framework and overview on the present study

In light of the beneficial health effects of natural elements, urbanneighborhoods with few health-relevant resources offer feweropportunities for recreation. Thus, inadequate availability of urbanvegetation and public green spaces can be considered environ-mental burdens and, therefore, potential health risks. These kindsof burdens might often co-occur with the health risks arising fromambient stressors. For example, as the number or size of urbangreen spaces increase in neighborhoods, physical environmentalquality improves by function of air pollutant absorption, noisereduction and microclimate regulation (Bolund & Hunhammar,1999; Kowarik et al., 2011; Langner, Kull, & Endlicher, 2011).Moreover, research findings suggest that such resources maycounterbalance the psychological effects of ambient stressors inurban neighborhoods (see Gee & Payne-Sturges, 2004, for a review;Leslie & Cerin, 2008). For example, perceived availability of nearbygreen areas was found to decrease annoyance reactions to trafficnoise (Gidlöf-Gunnarsson & Öhrström, 2007). Therefore, we arguefor an integrative framework (see Fig. 1) that takes into consider-ation both ambient stressors and lack of natural resources, as wellas their interplay, in order to enhance ecological validity of researchon neighborhood health effects.

To our knowledge, this is the first study to assess and comparethe relative relations and interplay of multiple ambient stressorsand lack of natural resources in regard to self-rated neighborhood-related health outcomes. Using Geographical Information Systems(GIS), we analyzed the spatial variability of two ambient stressors

Health Outcomes

ImpairedSatisfactionWith

Neighborhood

Poor HealthBehavior

PsychologicalSymptoms

ImpairedPhysicalHealth

ImpairedSatisfactionWith Life

EnhancedHealth Risk

l

s (i.e., ambient stressors and lack of natural resources) and neighborhood-related healthy way.

J. Honold et al. / Journal of Environmental Psychology 32 (2012) 305e317308

(traffic noise, air pollution) and one ecological resource (provisionwith public green space) in order to identify inner-city neighbor-hood street blocks in Berlin with high and low burden levels. Thesefactors were selected because, as the above-discussed literaturesuggests, they are the factors with most probable singular healtheffects. Afterward, a household questionnaire survey was conductedamong residents of these sites. The perceived levels of three otherubiquitous and locally relevant environmental burdens (van derMeer et al., 2011) were assessed as additional predictors for whichno suitable GIS-data exist: Litter and dirt in the public space,behavior-related noise and lack of urban vegetation.We hypothesizethat objective variations of environmental burdens are reflected insubjective environmental evaluations and in neighborhood-relatedhealth indicators. Moreover, we consider perceived levels of addi-tional non-varied environmental burdens for new insightsregarding the multiple-burden framework. Predictions of eitherindependent or interactive effects of multiple co-occurring burdens,as Lepore and Evans (1996) suggest, are impossible due to a lack ofliterature on burden-specific coping strategies. Thus, we investigatethe relative strength of each of the factors, the potential interactionsamong them, and their covariation in an exploratory way.

2. Method

2.1. Study areas

Our study was conducted in the German capital of Berlin, whichis divided in 12 districts and populated by about 3.4 millioninhabitants. As in most European cities, inner-city areas arecompact and densely populated by residents with varying levels ofsocial status. Late-19th century block developments dominate thelayout of these areas in Berlin. They consist of six-story housingunits with a front house, two side wings and a rear building with anenclosed backyard.

Street blocks were chosen as an appropriate neighborhood levelof analysis (cf. Dupéré & Perkins, 2007; Goldstein, 1989) in a four-step procedure. First, the latest versions of appropriate datasetson road traffic noise, traffic-related air pollution and provisionwithnear-residential public green space were selected from a DigitalEnvironmental Atlas.2 Second, we conducted a spatial analysisusing a Geographical Information System (ArcGIS). The threedatasets were classified into four levels of burden intensity3 each,then combined in a dataset, summed, and visualized in a mapcovering the entire urban area of Berlin.4 This allowed identifica-tion of inner-city blocks with a combination of the highest andlowest burden level in each of the three factors. The constellation ofenvironmental data is referred to as “high-burden” and “low-burden” street blocks throughout the paper and serves asa dichotomous neighborhood-level predictor. In addition, a dataseton various urban structure types was included in order to selectstreet blocks with comparable structural aspects (e.g., architecturalproperties of housing and within-block population density). We

2 The Berlin Senate Department for Urban Development (SenStadt, 2011)provides the Digital Environmental Atlas and comprises street block level data onvarious environmental burdens and resources. Most of these data cover the entireurban area.

3 Most of the datasets are environmental quality evaluations in nominal orordinal scale level with varying amounts of levels. Evaluations are aimed at humanhealth and correspond to legal bases. Metric exposure levels were not available. Forinterested readers, more detailed information on the spatial analysis and thedatasets used is available from the authors.

4 Contrary to traffic noise and green space data, which are provided as streetblock average values, air pollution is provided on a 5 m raster level and could,therefore, not metrically be integrated in the GIS analysis.

identified four inner-city districts containing a high-burden blockeach with a structurally comparable low-burden block in closeproximity (i.e., air-line distance of approximately 600e700 m).

The selected high-burden blocks are characterized by trafficnoise levels above 65 dB(A) (i.e., a total of road traffic, above-groundsubway, tram and railway traffic, averaged over all times of the dayand night). This threshold value was chosen as it is the daytimelimit considered acceptable in Europe (Commission of theEuropean Communities, 1996). Moreover, according to Germanenvironmental authorities the risk of myocardial infarctionincreases by 20% with chronic exposure to daytime noise levelsabove 65 dB(A) (cf. Umweltbundesamt, 2011). These blocks are alsoevaluated heavily burdened in regard to air pollution (SenStadt,2011). This means they exceed the EU limit for mean daily partic-ulate matter (PM10) of 50 mg/m3 more than 35 times a year and/orthe limit of a yearly average nitrogen dioxide (NO2) rate of40 mg/m.5 Moreover, there is less than 0.1 m2 of public green spaceper resident within a 500 m radius.6

The selected low-burden blocks have noise levels equal to orbelow 50 dB(A), are evaluated minimally burdened in regard to airpollution (SenStadt, 2011) and are provided with more than 6m2 ofpublic green space per resident within a 500 m radius. An exampleof one of the four study areas is displayed in Fig. 2. Table 1 gives anoverview of the characteristics of the eight blocks.

2.2. Sample

From 2000 surveys distributed to all eight street blocks, 428residents returned a completed questionnaire (21.4% response rate).Submissions were balanced between high-burden (n ¼ 215, 50.2%)and low-burden blocks (n¼ 213, 49.8%). Participants ranged from16to 91 years in age (M ¼ 39.5; SD ¼ 14.3). Tables 1 and 2 providefurther information on the sample characteristics. As displayed,women and highly educated people are overrepresented. However,education degrees in the population of Berlin are above Germanaverage (Kuhl, Pant, Rehkämper, Rockmann, & Wendt, 2009).According to the Federal Statistical Office (Destatis, 2010), thedegree of unemployed almost matches the city’s actual unemploy-ment rate of nearly 14% in 2009,while the 2009 foreigner rate of 14%in Berlin is underrepresented. Among those who indicated otherthanGerman nationality,most reported being European. Thirty-fivepercent of all participants indicated that they suffer from one ormore chronic stress-related physical symptoms such as painsymptoms (18%), gastrointestinal diseases (9%), hypertension/coronary heart diseases (10%), and asthma (6%), whereas only a fewparticipants reported frequent infectious diseases, cancer, diabetesmellitus and rheumatism. The mean individual raw scores ofpsychological symptom scales are displayed in the last two rows ofTable 3. Aligning these scores with the gender-specific norms(Franke, 2000), 33% reported a clinically relevant score in depres-sion, and 30% in anxiety. Comparisons of self-reported symptomswith officially diagnosed prevalence rates are certainly problematic.However, the rates of participants’ stress-relatedphysical symptoms

5 The air pollution dataset contains evaluations for PM10 and NO2 based ontraffic counts and classifies streets into four levels from minimally burdened toheavily burdened. In Berlin these two pollutants are regarded as the most serious inregard to human health (SenStadt, 2011). NO2 is a major source of indoor airpollution, can increase the risk of infection and emissions are not clearly droppingin German urban areas, as opposed to other inorganic gases. PM10 is among themost serious burdens in urban areas and suspected to increase the risk of cardio-vascular disease (Fiedler, Lüdecke, & Moriske, 2010; Lahmann, 1993).

6 Only green spaces >0.5 ha with a suitable shape, unrestricted accessibility andwithout major environmental pollution are incorporated into the dataset to ensurerestorative quality.

Fig. 2. Example of one of the four study areas with high vs. low burden levels. Block colors refer to high (1) vs. low (2) levels of traffic noise and no provision (1) vs. provision (2)with sufficient near-residential public green space. Shaded blocks indicate late-19th century block development structure. The degree of air pollution is depicted along the streetswith no indication of air pollution equivalent to minimal air pollution. Data source: Berlin Senate Department for Urban Development (SenStadt, 2011).

J. Honold et al. / Journal of Environmental Psychology 32 (2012) 305e317 309

seem below 2009 German prevalence rates, while participants withpsychological symptoms are rather overrepresented (Robert KochInstitut, 2011).

Fig. 3 displays reported reasons for residential choice in bothareas. It can be concluded that motivation for living in a high- orlow-burden area hardly differed. As an exception, participants fromhigh-burden blocks were more likely to choose their neighborhoodfor public transport connections (c2 (1) ¼ 4.39, p ¼ .04) and lesslikely for proximity to natural or quiet environments (c2 (1)¼ 17.19,p ¼ .00).

2.3. Measures of the surveyed variables

The following section describes relevant measures from thesurvey which consisted of three parts: 1) background variables(personal and situational factors), 2) perceptionof ambient stressorsand resources as individual-level predictors and appraisal ofstressors, and 3) neighborhood-related health outcomes. Eight

Table 1Subsample attributes of the eight street blocks chosen as study sites.

District Mitte Kreuzberg

Burden level High low High

n 53 40 51Response rate (%) 21.2 16.0 20.4Urban structurea 1 2 1Proportion of foreigners (%) 5e10 >30 20e<30Proportion of unemployed (%) <6 14e18 6e<10Social status indexb middle very low middle

Note. Statistical information on urban structure, proportion of foreigners/unemployed(SenStadt, 2011).

a 1 ¼ late-19th century block development with wings and rear buildings; 2 ¼ late-19b Neighborhood social status evaluation (SenStadt, 2011).

slightly different designs of the survey cover page enabled to allo-cate fromwhich of the eight blocks submissions came. Participantswere instructed to answer all neighborhood-related questions withrespect to their proximate living environment in order to avoid thedifficulties that have been associated with boundary-relatedneighborhood definitions (e.g., see Coulton, Korbin, Chan, & Su,2001). Proximate living environment was defined as the area ofa maximum 2-min-walk from participants’ home. The smallest unitof neighborhood is typically defined as an area of 5- or 10-min-walk(Kearns & Parkinson, 2001). However, based on German averagewalking speed (Morgenroth, 2008) we chose 2 min in order toconform to the measurement levels of the GIS data. Preferablyparsimonious scales published in English language were appliedwherever available, and repeated translation procedures were usedfor optimized adaptation to German language. Verbal anchors ofscales were chosen according to Rohrmann (1978) so as to ensureequidistance between scale points. Table 3 provides an overview ondescriptive statistics and psychometric properties.

Prenzlauer Berg Neu-Kölln/Treptow

low High low High low

42 56 62 55 6916.8 22.4 24.8 22.0 27.61 1 1 2 120e<30 5e10 5e10 >30 10e206e<10 14e18 14e18 14e18 10e14middle middle middle very low middle

and social status is based on data from the Senate of Urban Development Berlin

th century block-edge development with major changes.

Table 2Sample characteristics and distribution of background variables in low-burden(n ¼ 213) and high-burden (n ¼ 215) blocks.

Variable (missing values) Totalsample

High-burdenblocks

Low-burdenblocks

Female (2%) 61% 64% 61%Mean age (2%) 40 39 40Education (2%)Academic degree 50% 47% 54%University admission 25% 28% 23%Secondary school/ no degree 23% 23% 22%

Employment status (2%)Full-/part-time 61% 59% 61%Unemployed 11% 11% 10%Other statusa 28% 28% 28%

Non-German nationality (3%) 7% 6% 7%Marital status (3%)Single 68% 68% 67%Married 17% 17% 16%Separated/ divorced/ widowed 13% 12% 14%

Size of community where raised (2%)<20,000 33% 34% 32%20,000e100,000 15% 15% 15%100,000e1 Mio. 15% 17% 15%>1 Mio. 35% 33% 37%

MedicationSedatives (6%) 5% 6% 4%Antihypertensives (4%) 11% 11% 10%

Living alone (1%) 44% 42% 47%Living with children under 18 (1%) 18% 14% 21%Mean floor level (1%) 3 3 3Length of residency (1%)<one year 16% 16% 16%1e5 years 45% 45% 45%5e10 years 18% 20% 16%>10 years 20% 19% 22%

Outdoor facilityb (0%) 68% 57% 80%Windows facing street (2%) 73% 78% 69%

Note. Deviations are due to rounding total sample percentages.a Students/retired/homemakers/not working for other reasons.b Balcony/patio/terrace/private or shared garden.

J. Honold et al. / Journal of Environmental Psychology 32 (2012) 305e317310

2.3.1. Background variablesSocio-demographic characteristics were assessed by gender,

age, educational attainment, nationality, marital and employmentstatus, occupational position, size of communitywhere participants

Table 3Description of items and scales used in analyses.

Scale title No. of items Scale points n

Environmental perceptionAir quality 1 5 426Traffic noise 1 5 427Cleanliness 1 5 426Behavior-related noise 1 5 424Public green space 1 5 426Vegetation 1 5 427

Environmental appraisalAir pollution 4 5 427Traffic noise 4 5 422Litter and dirt 4 5 424Behavior-related noise 4 5 423

OutcomesNeighborhood satisfactiona 4 4 427Life satisfactiona 5 5 423General physical healtha 1 5 423Health behaviorb 3 2 425Depressionb 6 5 427Anxietyb 6 5 425

Note. High environmental perception means correspond to negative evaluations; high ea High values refer to good neighborhood-related health.b High values refer to poor health.c Inapplicable, as health behavior is considered a formative measure due to the heter

were raised, and use of relevant medication. Participants were alsoasked to indicate information on their housing situation such as co-habitants, length of residency, floor level, outdoor facilities(balcony/patio/terrace/private or shared garden), orientation tostreet and/or backyard, reasons for residential choice, and averagetime at home on weekdays.

2.3.2. Environmental perception and appraisalIn order to assess the perceived quality of all six environmental

factors of main interest (i.e., provision with public green space,vegetation, traffic-related noise, air quality, behavior-related noise,and cleanliness) participants were asked to judge the quality ofeach of these factors in their proximate living environment ona five-point Likert-scale. Higher ratings corresponded to betterenvironmental quality. Single item quality ratings were appliedbecause, according to the theoretical background, we did notexpect psychometric improvements from slightly differently wor-ded items. As an example, the item for perceived air quality “Howdo you judge the air quality in your proximate living environment?”could be answered from 1 ¼ very poor to 5 ¼ very good. Theperception of odor burden as an additional environmental qualityaspect was not metrically assessed because of the multidimen-sional nature of odorous quality. Instead, participants were askedwhether unpleasant odors were regularly present in their proxi-mate living environments and, if yes, to describe the odor’s source.

Environmental stress appraisals were assessed only for theambient stressors, as lack of resourceswas theoretically expected toimpact health by different pathways than by stress appraisal. Assuggested in the environmental annoyance literature (Langdon,1987; Lazarus, 1990), four items per stressor were used to assessthe nuances of emotional reactions to each stressor. Participantswere requested to indicate, on 5-point scales, the degree eachstressor in their proximate living environment impacted their well-being, annoyed them inside their dwelling, annoyed themoutdoors, and how much they felt threatened in regard to health(with 1 ¼ not at all impacted/annoyed/threatened and 5 ¼ very muchimpacted/annoyed/threatened). Terminology of two environmentalfactors was changed here. That is, “air quality” was exchanged by“air pollution” and “cleanliness”was exchanged by “litter and dirt”.As displayed in Table 3, internal consistencies allowed for usingamean appraisal scale score from these four items for each stressor.

M (SD) Skew-ness Kurtosis Rel. (alpha)

1.80 (0.82) �0.42 0.472.11 (1.17) �0.06 �0.852.09 (0.90) �0.27 �0.401.71 (0.96) �0.40 �0.221.20 (0.90) �0.58 0.191.52 (0.92) �0.45 �0.20

2.55 (0.96) 0.42 �0.23 0.892.85 (1.04) 0.18 �0.69 0.852.41 (0.89) 0.44 �0.17 0.782.31 (0.99) 0.71 �0.21 0.86

2.99 (0.61) �0.66 0.11 0.853.51 (0.75) �0.43 0.08 0.863.52 (0.86) �0.22 �0.180.97 (0.84) 0.47 �0.56 i.a.c

1.68 (0.81) 1.53 2.18 0.841.66 (0.64) 1.28 1.57 0.75

nvironmental appraisal means correspond to high stress appraisals.

ogeneous nature of the construct (cf. MacKenzie, Podsakoff, & Jarvis, 2005).

Fig. 3. Comparison of reasons for choosing residence. Percentage of participants from low-burden versus high-burden street blocks who indicated the corresponding group as oneof two reasons for choosing the place of residence. *p < .05; ***p < .001.

J. Honold et al. / Journal of Environmental Psychology 32 (2012) 305e317 311

2.3.3. Outcomes7

Neighborhood satisfaction was assessed with a German adap-tation (Feuersenger, 2004) of a four-item scale from Weidemann,Anderson, Butterfield, and O’Donnell (1982). The items directlyinquire into the degree of satisfaction with the living environment,e.g. “How satisfied are you with living here?” The scale was chosenbecause direct neighborhood satisfaction measures have provenmore valid than indirect scales (Amérigo & Aragonés, 1990). As inthe original version, items could be answered on four-point scaleswith item-dependent verbal anchors and high values indicatinghigh satisfaction.

Life satisfaction was assessed with a scale developed by Diener,Emmons, Larsen, and Griffin (1985). It assesses how participantsjudge their own life as awhole. It consists of five items, such as “Theconditions of my life are excellent,” that had to be answered ona five-point scale (1 ¼ do not agree at all and 5 ¼ very much agree).Similar to neighborhood satisfaction, overall judgments should bepreferred over domain-specific evaluations, since individuals mayplace different values on certain domains (cf. Diener et al., 1985).According to an expert panel discussion (Tesch-Römer, Schupp,Walper, Knabe, & Junginger, 2010), affective measures of subjec-tive well-being are more sensitive to daily variations than cognitiveevaluations. Therefore, a cognitive measure was preferred.

Health behavior was assessed using a revised version of an indexfrom Feldman and Steptoe (2004). Participants were asked toindicate if they were a) currently smoking, b) consuming two ormore units of alcoholic beverages on at least three days of theweek,and c) carried out any vigorous physical activity like running, sportsor dancing within the last two weeks. In accordance with theoriginal authors, we created a composite index by counting each

7 The sequence of scales in the original questionnaire deviated from the depictionhere in that three outcome variables (i.e., neighborhood satisfaction, life satisfac-tion, general physical health) were presented between background variables andenvironmental perception/appraisal. This sequence was chosen because satisfactionmeasures were expected to be most susceptible to emotional priming bias, whereassymptom lists and items should be least affected.

health-comprising response as one point (with c reversely coded).Thus, index scores could be treated as a metric variable and wouldrange from 0 (good health behavior) to 3 (poor health behavior).

General physical health was assessed with a single item fromthe German version of the SF-36 health survey (Bullinger &Kirchberger, 1998), as global one-item health ratings are goodpredictors of unspecific somatic symptoms such as pain, dizzinessor problems with the respiratory system (e.g., Wallenius, 2004) andof mortality (Idler & Benyamini, 1997). Participants were asked howthey would describe their health status in general on a scale frompoor (1) to excellent (5). In addition, we included a check-off list ofeight physical symptoms that have been linked to chronic stress(i.e., chronic pain symptoms, gastrointestinal complaints, frequentinfectious diseases, hypertension/coronary heart diseases, cancer,diabetes mellitus, rheumatism, and asthma). The design of this listwas guided by the literature (e.g., Carlson, 2004; Dougall & Baum,2001; Westert et al., 2005).

Psychological symptoms were measured using two scales fromthe German adaptation (Franke, 2000) of the Brief Symptom Inven-tory by Derogatis (1993), namely, depression and anxiety. Thesescales were chosen because they represent symptoms associatedwith different kinds of environmental stress and relate to commonemotional stress reactions according to our literature review. Theinventory lists various problems and discomforts and asks partici-pants to indicate how intense they were disturbed within the sevenlast days e from “not at all” (1) to “very intense” (5).

2.4. Procedure

After posting announcement flyers through the study areas,2000 questionnaires were equally distributed in each of the eightblocks in August 2009. Thus, 250 households in each block receiveda questionnaire. The survey could be completed in 25e30 min. Anaccompanying information letter invited residents from age 18 toparticipate in a study on the perception of environmental condi-tions in residential areas and on general well-being of Berlin resi-dents. Letters did not indicate any reasons for selection of the site.

Table 4Correlations of age, environmental Perception items and appraisal scales withCriteria: Neighborhood Satisfaction (NS), Life Satisfaction (LS), General PhysicalHealth (GH), Health Behavior (HB), Depression (D), and Anxiety (AN).

NSa LSa GHa HBb Db ANb

Age 0.00 �0.08 �0.47** 0.04 0.00 �0.09Environmental perceptionAir quality �0.39** �0.23** �0.20** 0.14** 0.17** 0.14**Traffic noise �0.28** �0.07 �0.09 0.16** 0.03 0.03Cleanliness �0.36** �0.11* �0.18** 0.08 0.14** 0.13**Behavior-related noise �0.40** �0.16** �0.07 0.11* 0.14** 0.15**Public green space �0.40** �0.13** �0.11* �0.01 0.09 0.05Vegetation �0.40** �0.14** �0.01 �0.02 0.03 0.03

Environmental appraisalAir pollution �0.35** �0.14** �0.15** 0.08 0.20** 0.20**Traffic noise �0.29** �0.10* �0.09 0.11* 0.08 0.13**Litter and dirt �0.29** �0.11* �0.15** 0.05 0.12* 0.12*Behavior-related noise �0.36** �0.21** �0.18** 0.08 0.18** 0.24**

Note. High environmental perceptions correspond to negative evaluations; highenvironmental appraisals correspond to high stress appraisals.*p < .05; **p < .01.

a High values refer to good well-being.b High values refer to poor well-being.

J. Honold et al. / Journal of Environmental Psychology 32 (2012) 305e317312

As an incentive for participation, addressees could fill out andreturn a lottery ticket within four weeks for a dinner voucher ata restaurant of their choice. In addition, they were provided a post-paid envelope, were offered a report on results, and asked to namesuggestions concerning the improvement of their neighborhoodthat would be summarized and forwarded to local authorities.

2.5. Statistical analyses

All 428 returned surveys were included in comparisons betweenhigh- and low-burden areas since information on location of resi-dence was available for each participant. In order to control forpotential biases due to background variables, the characteristics ofparticipants from high-burden and low-burden areas displayed inTable 2 were compared using Pearson’s chi-square tests for dichot-omous variables, loglinear analyses for nominal variables with threecategories, and analyses of variance (ANOVA) formetric variables. Nosignificant differences in background variableswere found,with twoexceptions: According to self-reports more residents from low-burden blocks have apartments with a balcony, terrace, patio orshared garden (c2 (1) ¼ 25.67, p ¼ .00) and apartments withoutwindows facing the street (c2 (1) ¼ 4.33, p ¼ .04). Environmentalperception and appraisal in high-burden versus low-burden blockswere compared using ANOVA. In order to test the assumption thatresidents from high-burden blocks would report poorer health thanresidents from low-burden blocks, logistic regressionswere used fordichotomous and analyses of covariance (ANCOVA) for metricoutcome indicators with age as a covariate to reduce error variance.Age was integrated in all analyses since it is associated with poorhealth symptoms and neighborhood satisfaction (Carp& Carp,1982).Age effects are not of particular interest in the current study and arenot reported unless necessary to clarify effect sizes. Since verbalanchors of each scale were equidistant, all parametric assumptionsfor ANOVA and ANCOVA were met except normality and homoge-neity of variance in some cases. However, the F-statistic is quiterobust to violations of both assumptions when group sizes are equal(cf. Field, 2009), as is the case with these groups.

Hierarchical regression analyses (cf. Cohen, Cohen, West, &Aiken, 2003) were applied to test whether outcomes can be pre-dicted better bymultiple concurring environmental burdens, ratherthan by a singular burden alone. Subjective perceptions of envi-ronmental stressors and resources were chosen as predictors. Thecomplete samplewas included in amultiple forced entry regressionperformedwith all environmental perception variables assessed foreach of the outcome variables in order to reduce the amount ofpredictors for hypothesis testing. B ¼ 0.1 was determined to be theminimally required strength of influence. Accordingly, a hierarchicalregressionwas runwith age entered in the first step, the predictorssimultaneously in the second step, their interaction terms in thethird step, and higher-order interaction terms in the fourth stepwhen necessary. The predictors were z-transformed to counter-balance different standard deviations and to reduce multi-collinearity (Jonas & Ziegler, 1999). Normality of errors andcollinearity diagnoses indicated no violations of assumptions.

Throughout the following chapter, environmental perceptionindicators are presented reversely coded so that high values ofperception and appraisal correspond to negative environmentalevaluations.

3. Results

3.1. Descriptive results

Table 3 provides an overview of mean perceptions andappraisals. In regard to odor burdens which were not assessed in

ametric way, 29% of the total sample (n¼ 122) indicated perceivingunpleasant odors regularly. Odors came from various sourcesincluding odors caused by neighbors’ behaviors (29% of thissubsample), traffic exhaust fumes (21%), litter and dog excrements(19%), and open waters or canalizations (10%). Correlations ofperception items and appraisal scales with criteria and age arepresented in Table 4. For clarity, intercorrelations within perceptionitems or appraisal scales are not displayed. Among perceptions,they ranged from r¼ .16** (lack of green space and behavior-relatednoise) to r¼ .51** (traffic noise and air pollution) and indicated thatbetter perceived quality in one factor was correlated with betterperceived quality in the other. Among appraisals, intercorrelationshad accordant directions, ranging from r ¼ .43** (air pollution andlitter and dirt) to r ¼ .69** (air pollution and traffic noise).

3.2. Comparisons of high-burden and low-burden neighborhoodblocks

As shown in Table 5, the perceptions of air pollution, traffic noiseand provision with near-residential public green space differsignificantly, with traffic noise differentiating most clearly. It wasalso confirmed that residents from high-burden blocks appraise airpollution and traffic noise more negatively. Beyond the objectivelyvaried factors, residents from high-burden blocks reported living insomewhat dirtier (F(1, 424)¼ 4.21, p¼ .04, partial h2 ¼ .01) and lessvegetated (F(1, 425) ¼ 13.63, p ¼ .00, partial h2 ¼ .03) neighbor-hoods and perceived more incidences of odor burdens (34 vs. 23%;c2 (1)¼ 6.15, p¼ .01, F¼ .12). However, they did not appraise thesenon-varied environmental factors significantly more negatively.

Results on comparisons of neighborhood-related health indi-cators in both areas are also displayed in Table 5. Contrary to thehypotheses, residents from high-burden neighborhoods did notreport lower life satisfaction, poorer general physical health ormore psychological symptoms. Neither did they suffer from one ormore stress-related physical symptoms more often (37 vs. 33%; c2

(1) ¼ 0.71, p ¼ .40). However, they indicated being significantly lesssatisfied with their neighborhood and behaving significantly lesshealthy. To break down the health behavior index, chi-squarecomparisons were significant in regard to nicotine consumption(43 vs. 29%; c2 (1) ¼ 8.39, p ¼ .00, F ¼ .14) and physical exercise(32% from high-burden vs. 20% from low-burden blocks had notcarried out any vigorous physical activity in the preceding twoweeks; c2 (1) ¼ 7.15, p ¼ .01, F ¼ .13). Alcohol consumption did not

Table 5Results from ANOVA comparing environmental perceptions and appraisals amongresidents from High-burden blocks (HBB) versus Low-burden blocks (LBB) and fromANCOVA comparing outcomes Likewise.

LBBmean

HBBmean

F df p partialh2

Environmental perceptionAir quality 1.57 2.02 34.02 1, 424 0.00 0.07Traffic noise 1.51 2.71 154.50 1, 425 0.00 0.27Green space 0.97 1.43 28.66 1, 424 0.00 0.06

Environmental appraisalAir pollution 2.31 2.78 27.64 1, 425 0.00 0.06Traffic noise 2.58 3.12 31.35 1, 420 0.00 0.07

OutcomesNeighborhood satisfactiona 3.05 2.93 4.59 1, 417 0.03 0.01Life satisfactiona 3.44 3.47 0.21 1, 414 0.64 0.00General physical healtha 3.47 3.54 0.61 1, 414 0.44 0.00Health behaviorb 0.81 1.13 14.96 1, 413 0.00 0.04Depressionb 1.72 1.66 0.47 1, 417 0.50 0.00Anxietyb 1.67 1.64 0.29 1, 416 0.59 0.00

Note. High environmental perception and appraisal means correspond to negativeevaluations.

a High values refer to good neighborhood-related health.b High values refer to poor health. Only estimates of interest are presented.

Significance levels are two-tailed.

J. Honold et al. / Journal of Environmental Psychology 32 (2012) 305e317 313

differ significantly (38 vs. 31%; c2 (1) ¼ 2.34, p ¼ .13). Differences inindicators of poor health (general physical health, psychologicaland physical symptoms) were also compared in a subsample ofthose who had been living in these blocks for at least one year. Assome of the residents from both burden level areas had apartmentswithout any windows facing the street, these participants wereexcluded and comparisons were repeated. To control for a potentialexposure intensity effect, comparisons were also performed fora subgroup of those who indicated to spend, on average weekdays,at least half day at home. None of these analyses revealed signifi-cant findings.

Additional ANCOVA with gender, education, and employmentstatus (see Table 2) as a second factor for all outcome variables didnot affect the significance and effect size of burden level andrevealed no significant interactions, with one exception: Burdenlevel and employment status significantly interacted in regard tohealth behavior. That is, employed participants and the other statusgroup (students, retired, etc.) behaved less healthy in the high-burden blocks, while unemployed participants did not differsignificantly between both burden level areas. To summarize, GIS-based variations in burden levels are reflected in residents’ envi-ronmental perceptions and appraisals. Residents from high-burdenblocks report poorer health behavior and are less satisfied withtheir neighborhoods.

3.3. Co-occurrence of perceived multiple stressors and lack ofresources

Multiple hierarchical regressions analyzing the interplay of allenvironmental factors on an individual level revealed the followingresults: Neighborhood satisfaction was explained by perceivedprovision with public green space (b ¼ �0.21, p ¼ .00), behavior-related noise (b ¼ �0.21, p ¼ .00), air quality (b ¼ �0.16, p ¼ .00),cleanliness (b ¼ �0.15, p ¼ .00), and vegetation (b ¼ �0.14, p ¼ .01)(R2 ¼ .34***, n ¼ 413). None of the interaction terms or higher-orderinteractions were significant. Life satisfaction could only beexplained by perceived air quality (b ¼ �0.19, p ¼ .00, R2 ¼ .06***;n ¼ 412), whereas poor health behavior was merely related toperceived traffic noise (b¼ 0.12, p¼ .03, R2¼ .04**; n¼ 412). Generalself-ratedhealthwasexplainedbyage (b¼�0.47,p¼ .00;R2¼ .22***)and air quality (b¼ �0.22, p¼ .00; DR2 ¼ .04***) (n¼ 411). Likewise,

air quality was the only environmental factor related to depression(b ¼ 0.13, p ¼ .01, R2 ¼ .04**; n ¼ 413) and anxiety (b ¼ 0.11, p ¼ .03,R2 ¼ .03**; n ¼ 412). In order to explore the effects of socio-demographic variables, separate regression analyses were per-formed for gender, education, and employment status subgroups. It isbeyond the scope of this article to report them in detail. In short,regarding neighborhood satisfaction, the strength of influence of thesignificant predictors varied in some groups, while traffic noiseremained non-significant in all analyses. Air quality remained thedominant predictorof life satisfaction, general health, depressionandanxiety. In addition, cleanliness was positively related to depressionand anxiety in women and the low-educated group. Finally, whileenvironmental perception was unrelated to health behavior inunemployed participants, health behavior of employed participantsand the other status group could be predicted from traffic noise andair quality. To summarize, neighborhood satisfaction as a measure ofneighborhood-related health could be predicted from additively co-occurring environmental burdens, whereas air quality plays a crucialrole in predicting more general self-rated health. It is interesting tomention that among the four air pollution appraisal items, the degreeof annoyance at home correlated higher with the relevant healthoutcomes (i.e., neighborhood satisfaction, life satisfaction, self-ratedhealth, depression, anxiety) than impaired well-being, annoyanceoutdoors or subjective health threats.

4. Discussion

4.1. Multiple neighborhood burdens and neighborhood-relatedhealth outcomes

The aim of the present study was to analyze the relationsbetween multiple neighborhood burdens and health indicators,incorporating both ambient stressors and lack of environmentalresources. A spatial analysis using environmental datasets on airand noise pollution and on provision with public green space hel-ped determine study sites. A household questionnaire survey wasconducted in street blocks with high and low burden levels. Thestudy yielded the following main results: First, objective variationsin environmental burden levels are reflected in residents’ percep-tions and appraisals of these environmental factors. Second, theseobjective variations are reflected in self-reported health behaviorand slightly in neighborhood satisfaction. Third, neighborhoodsatisfaction can be better predicted from perceived levels ofmultiple, independently co-occurring environmental stressors andresources than from the objective variation of fewer burdens.Fourth, general health indicators are associated with perceived airquality. In the following section these main results are discussed inmore detail.

4.1.1. Residents’ perceptions and appraisals of varied environmentalburdens

As hypothesized, variations in traffic noise, air pollution andprovision with green space among inner-city neighborhood blocksin available environmental datasets are reflected in residents’perceived levels of these factors. Residents distinguished trafficnoise burden most strongly, but they were also able to distinguishvaried levels of traffic-related air pollution and provisionwith near-residential public green space. Thus, this study validates results ofspatial analyses of environmental stressors and resources asa valuable tool for research in environmental psychology andsimilar disciplines.

Moreover, these data suggest that multiple burdens fromdifferent sources co-occur spatially and temporarily. This wasalready found for factors usually available in environmental data-sets such as noise from different sources, air pollution, lack of green

J. Honold et al. / Journal of Environmental Psychology 32 (2012) 305e317314

space and climatic conditions (e.g., Pearce, Richardson, Mitchell, &Shortt, 2010). In addition, according to our data residential areaswith a high level of such burdens may also be affected by furtherstressors (in this case, litter and dirt and a high frequency of odorburdens) and by a lack of environmental resources for recreationother than public green spaces such as urban vegetation, whichmay worsen the impacts of the stressful stimuli.

We also confirmed that varied levels of traffic noise and airpollution are reflected in residents’ stress appraisals. That is, resi-dents from high-burden blocks felt more impaired, annoyed orthreatened by traffic noise and air pollution compared to residentsfrom low-burden blocks and may therefore be unable to habituateto these ambient stressors. In congruence with the World HealthOrganization that specifies annoyance of environmental burdens asan adverse health effect (Berglund, Lindvall, & Schwela,1999), theseresidential areas might pose a disadvantage to their residents’health.

4.1.2. Varied environmental burdens and self-reported healthbehavior

As hypothesized, residents from high-burden blocks reported toengage in poorer health behavior, with the exception of unem-ployed residents. After controlling for the potentially confoundingeffects of age, gender, and degree of education, participants fromhigh-burden blocks reported consuming more nicotine, exercisingless and consuming marginally more alcohol. In the literature,spatial patterns of health behavior in urban areas have mostly beenattributed to differences in neighborhood social status, larger-scalevariations in health education, or density of substance providers(D.A. Cohen et al., 2003; Feldman & Steptoe, 2004; Ross, 2000;Taylor et al., 1997). However, in our study, these explanations can beruled out. As shown in Table 1, the comparison of high-burden andlow-burden blocks is not systematically biased by differences inneighborhood social status. Moreover, differences in healtheducation or substance providers are unlikely due to the closespatial proximities of the compared blocks. Our results contradicta study from Steptoe and Feldman (2001) who did not find anyrelationship between perceived neighborhood stressors and healthbehavior. As these authors did not consider objective burden levels,we assume that the difference in health behavior in our data maybe attributable to physical environmental conditions rather thancognitive factors. The higher incidence of smoking in high-burdenblocks coincides with an experimental study that found smokingbehavior to increase with higher levels of noise (Cherek, 1985).Moreover, in the regression analysis of the relationship betweenthe perceived intensity of multiple factors and health behaviortraffic noise andewhen unemployed participants were excludede

air pollution were significant predictors. Taking into account ourtheoretical framework, this finding may point to a strategy ofresidents from high-burden blocks to cope with environmentalstress. Moreover, the lower extent of physical activity found heremay be due to a lack of environmental affordances (cf. Gibson,1977)not only in terms of stressful conditions but also in terms of a lack ofpublic green spaces and vegetation, which were shown to stimulatephysical activity (Sullivan et al., 2004).

4.1.3. Prediction of neighborhood satisfactionThe expected difference in neighborhood satisfaction between

residents of both burden level areas was confirmed; however, theeffect was small. Our results indicate that neighborhood satisfac-tion can be better predicted from perceived levels of multiple,independently co-occurring environmental stressors and resourcesthan from the objective variation of fewer burdens. In regressionanalysis, perceived levels of air quality, provision with public greenspace, behavior-related noise, and cleanliness explained 34% of the

variance, with additive and comparably strong contributions. Theeffect size is remarkable, as other factors generally assumed to havestronger effects on neighborhood satisfaction (e.g., upkeep,perceived economic value or perceived safety; Francescato, 2002;Hur & Morrow-Jones, 2008; Ringel & Finkelstein, 1991) were notincluded. With respect to the theoretical framework, the result mayindicate that the difference in neighborhood satisfaction betweenhigh-burden and low-burden blocks is due to the perceiveddifferences in air quality and provisionwith green space rather thantraffic noise. According to Lepore and Evans (1996), the additiveeffects indicate that these five environmental burdens demanddifferent coping resources or strategies. To our knowledge, nostudies have yet been published on this issue. Our finding supportsearlier research approaches that explained neighborhood satisfac-tion using additive stress scores (e.g. Handal, Barling, & Morrissy,1981). The benefit of our approach is that it enables to clarifywhich factors to tackle in interventions for sustainable urbandevelopment.

4.1.4. Environmental factors and general health indicatorsRegression analyses indicated that perceived air quality was the

only environmental factor related to life satisfaction, general self-rated health, depression, and anxiety in the total sample. Thisreplicates earlier findings on a relationship between air pollutionand impaired mental health (cf. Evans, 2003). As the annoyance-at-home-item correlated strongest with these outcomes it can beassumed that subjectively affected participants felt they could notescape from poor air quality even in their own dwelling. A lack ofperceived control over environmental stressors enhances theirdetrimental effects (Robin, Matheau-Police, & Couty, 2007), whichcould explain the relation between perceived low air quality andmental health. However, contrary to our prediction, life satisfactionand poor health symptoms were not related to objective burdenlevels. Thus, the relation between air quality and mental healthmight be more strongly influenced by other variables than byobjective levels of NO2 and PM10. Further research is needed toclarify this aspect.

To summarize, our results suggest the following: Residents frominner-city neighborhoods with high levels of traffic noise, airpollution and little provision with public green space might be atgreater health risk in comparison to lower-burden neighborhoodsdue to enhanced stress appraisals and differences in healthbehaviors. Moreover, neighborhood satisfaction can be additivelypredicted from perceived levels of multiple burdens. Finally,perceived air pollution plays a crucial role in predicting generalhealth.

4.2. Limitations

Concluding that neighborhoods with the physical conditionsstudied here (i.e., traffic noise levels above 65 dB(A), high levels ofNO2 and PM10, no provision with sufficient public green spaceswithin a 500 m radius) do not pose a risk to their residents’ generalhealth would be premature due to some limitations of the presentstudy. The response rate of 21% is quite low, albeit on average incomparison with other recent residential surveys without indi-vidual financial or similar compensations (e.g., Kearney, 2006;Leslie & Cerin, 2008; Steptoe & Feldman, 2001). A sample biasarising from higher non-responses of more affected residents isunlikely due to the well-balanced responses from high- and low-burden blocks. However, judging from degrees of education andforeigners, our sample under-represents lower social status groupsthat can be expected to be generally more vulnerable to suffer frompoor mental or physical health. The lack of variance in social status

J. Honold et al. / Journal of Environmental Psychology 32 (2012) 305e317 315

limited the statistical power to detect adverse health effects inresidents with low social status.

Another limitation is related to the environmental data used inthis study: While noise pollution data is available on a 5 m rasterlevel, air pollution and public green space are only available onhigher-level averages which did not allow for establishing metricrelationships between objective and subjective burden levels andmore precise burden estimations for each participant.

Finally, causal inferences are impossible due to the cross-sectional design. Unaccounted third variable influences or causalpathways in the opposite directions cannot be ruled out. Forexample, the finding that residents from high-burden blocksengage in poorer health behavior can alternatively be explained byself-selection processes due to differences in health consciousness:Highly health-conscious people who are physically more active andwho consume less nicotine and alcohol might also be more con-cerned about health risks arising from environmental pollution.Therefore, they may choose residential areas with lower perceiv-able burden intensities.

4.3. Conclusion

Our study is the very first to investigate both multiple stressorsand lack of environmental resources and their interplay on anindividual, as well as on a neighborhood street block level. Ourapproach has proven worthwhile for multiple reasons. Uniquepartitions of variance in neighborhood satisfaction could beexplained by multiple burdens. Moreover, according to partici-pants’ reports, multiple burdens (namely air and odorous pollution,traffic noise, lack of green space and urban vegetation, and litter)co-occur spatially and temporarily in neighborhood street blocks.Hence, our findings highlight the importance of an integrativemultiple-burden framework, such as the one we propose in Section1.3, in future research. Studies on hot spots of environmentalvulnerability, urban health risk and environmental justice shouldalso take into consideration less-examined factors such as litteringdegrees, odor burdens, behavior-related noise and lack of urbanvegetation. Data on the spatial dispersion of such factors are notavailable for many cities, including Berlin. If city administrationsincreased the diversity of environmental burden datasets andintegrated them with health reports and social developmentmonitoring, it would be a fruitful addition and could be used tobetter evaluate health-relevant neighborhood qualities. Further-more, the finding that neighborhood satisfaction can be predictedfrom multiple stressors and resources implies urban developmentprojects, which improve several factors simultaneously, should beprioritized. For example, small patches of green (e.g., road side orvertical vegetation) are effective and inexpensive ways to enhancethe amount of urban vegetation and to ameliorate air quality at thesame time (Kowarik et al., 2011).

The finding that residents in neighborhoods with high levels oftraffic and little provision with public green spaces behave lesshealthy can be applied in sustainable urban development in bothhealth prevention strategies and urban planning. Billboard healthcampaigns, informative household flyers, or special healthprevention programs should be targeted specifically in such high-burden areas. In addition, the results stress the importance ofproviding residents with sufficient public green spaces withina 500-meter radius to their homes. If public green space cannot beadded in areas that lack them, it should be compensated by othermeasures to involve residents in regular physical exercise. Thismight be achieved by providing more gyms, sport halls or sportprograms, and by supporting sport unions. In addition, urbanbrownfields and wastelands can function like parks if specificdesign aspects are considered (Hofmann, 2011).

Our results may be generalized to other cities to some degree, asthe city of Berlin does not have extreme levels of the burdensstudied here (cf. European Environment Agency, 2009). Our studydesign is based on environmental data that are classified accordingto EU standards (cf. SenStadt, 2011) and are available in mostEuropean cities. Moreover, we used predominantly standardizedscales for data collection. Thus, comparative studies in differenturban areas are possible and may allow new insights.

Finally, comparing the effect sizes of outcomes predicted fromobjective environmental data versus subject’s perceptions high-lights the importance of taking into account subjective neighbor-hood evaluations from city residents, in addition to objectiveevaluations based on environmental data. This is also importantsince urban designers, architects, and municipal policy makerscannot anticipate residents’ subjective evaluations (Brucks, 2012a,2012b; Harloff & Burkhardt, 1993). Residential surveys can be usedto identify priorities in local needs for improvements and evaluatesocial urban development programs or urban design projects onsmaller or larger scales. Combining both approaches (that is,enhancing the diversity of environmental data and integratingsubjective perspectives of users) might be the most promisingapproach in defining priorities for intervention programs withinurban areas in order to ensure healthy living environments for allcity residents.

Acknowledgments

This research was funded by Deutsche Forschungsgemeinschaft(DFG). In addition, we especially thank Jörn Welsch and ThomasSchneider from the Senate Department of Urban Development ofBerlin for data provision, as well as our colleague Cornelius Senf forassistance with the spatial analysis.

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