Pickett_Multilevel Analyses of Neighbour Hood Socioeconomic Context and Health Outcomes

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Multilevel analyses of neighbourhoodsocioeconomic context and health outcomes: acritical review

K E Pickett, M Pearl

AbstractPurpose Interest in the eVects of neighbourhood or local area social characteris-tics on health has increased in recentyears, but to date the existing evidence has

not been systematically reviewed. Multi-level or contextual analyses of socialfactors and health represent a possible

reconciliation between two divergent epi-demiological paradigmsindividual riskfactor epidemiology and an ecological

approach.Data sources Keyword searching of

Index Medicus (Medline) and additionalreferences from retrieved articles.Study selectionAll original studies of theeVect of local area social characteristics

on individual health outcomes, adjustedfor individual socioeconomic status, pub-lished in English before 1 June 1998 andfocused on populations in developed coun-tries.Data synthesis The methodologicalchallenges posed by the design andinterpretation of multilevel studies of localarea eVects are discussed and resultssummarised with reference to type ofhealth outcome. All but two of the 25reviewed studies reported a statistically

significant association between at leastone measure of social environment and ahealth outcome (contextual eVect), afteradjusting for individual level socioeco-nomic status (compositional eVect). Con-textual eVects were generally modest andmuch smaller than compositional eVects.Conclusions The evidence for modestneighbourhood eVects on health is fairlyconsistent despite heterogeneity of studydesigns, substitution of local area meas-ures for neighbourhood measures andprobable measurement error. By drawingpublic health attention to the health risksassociated with the social structure and

ecology of neighbourhoods, innovativeapproaches to community level interven-tions may ensue.(J Epidemiol Community Health 2001;55:111122)

The association of health status and many dis-eases with socioeconomic status has been sowidely demonstrated in varied populations1

that adjustment for socioeconomic status hasbecome routine in epidemiological analyses.2

Health status is related to socioeconomic statusacross the socioeconomic gradient; evenamong populations with relatively high socio-

economic status, the most advantaged havebetter health status than the less advantaged.3

Population inequalities in disease are notgenerally accounted for by any known combi-nation of individual genetic and environmentalrisk factors, and must therefore be attributableto other unmeasured factors, some of whichmay operate at an aggregate level (see variouspublications2 411 for discussions). Winkelsteinhas pointed out that ecological factors may bethe most important determinants of the healthand disease status of a population.12 Theneighbourhoods in which people live may

influence health, operating through suchmechanisms as: the availability and accessibil-ity of health services; infrastructure deprivation(lack of parks, stores selling healthy foods ataVordable prices, etc); the prevalence ofprevailing attitudes towards health and healthrelated behaviours; and stress and a lack ofsocial support.8

Although there is an established tradition ofinquiry into the impact of neighbourhood fac-tors on sociological outcomes, such as edu-cational attainment and labour marketopportunities,1315 neighbourhood variation inhealth has received less attention in epidemiol-ogy until recently. In part this is because of the

intractability of the ecological fallacy whengroup level data are used to infer individualdisease risk, and also because of a disciplinaryfocus on individual risk factors through muchof this century.9 16 An increasing interest insocietal influences on individual health status,along with improved statistical techniques forcombining group level and individual level fac-tors in regression models has spurred interestin contextual research in epidemiology.6

The statistical issues involved in multilevelstudies have been well described,17 and hierar-chical regression analysis is becoming widelyaccepted as the appropriate tool for examininggroup level eVects on individual health. Todate, there has been no published summary ofthe results of multilevel epidemiological studiesand the literature reviews included with mostpublished analyses have been incomplete. Thevalidity and generalisability of neighbourhoodeVects remain open to question, and as yetthere has been little empirical investigation ofthe causal pathways by which social environ-ments translate into biological states of healthand disease. Indeed, it is probable thatneighbourhood or contextual eVects will them-selves be contextual, and that both the factorsthemselves and the magnitude of their eVectswill be context dependent. In this paper we

J Epidemiol Community Health 2001;55:111122 111

Department of HealthStudies, University of

Chicago, 5841 SouthMaryland Avenue, MC2007, Chicago, IL

60637, USAK E Pickett

Department of Familyand Community

Medicine, Universityof California, SanFranciscoM Pearl

Correspondence to:Dr Pickett([email protected])

Accepted for publication28 August 2000

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seek to summarise the epidemiological litera-ture, paying particular attention to method-ological issues inherent in multilevel studies, sothat the literature can be viewed in its entirety.

Methods

Studies were identified via keyword searchingon Medline using the terms multi-level, socialclass, neighborhood, socioeconomic factors,

health outcomes, and additional studies wereretrieved from reference lists. Inclusion criteriafor studies were: (1) published in English inpeer reviewed journals before June 1998, (2)study population in a developed country, (3)outcome of physical or mental health or healthbehaviour, measured at the individual level, (4)multilevel studies with socioeconomic infor-mation measured at both the individual leveland area level. There is a large body ofliterature from the sociological and demo-graphic literature covering community eVectson fertility and sexual behaviour that is notcovered in this review (see for example Brews-ter18 and Grady et al19). The growing epidemio-logical literature on income inequality (see for

example2023) that is concerned with estimatingthe eVect of diVerentials in socioeconomic sta-tus rather than the eVect of low socioeconomicstatus in itself is also excluded, as it has meth-odological issues deserving of separate treat-ment.

We identified 25 studies using these criteria(table 1). We categorised results by health out-come: mortality, morbidity (only one studyexamined mental health) and health behav-iours. Five studies had results in more than onecategory and are cross referenced in table 1.Thirteen studies were conducted in USsamples, nine in the UK, two in the Nether-lands and one in Finland.

Methodological issues in studyingneighbourhood social factorsDEFINING AND MEASURING NEIGHBOURHOODAll but two24 25 of the studies used geographicalboundaries, developed for the census or otherpolitical purposes, as proxies for actual com-munities or neighbourhoods (table 1). Thechoice of political boundaries permits straight-forward linkage with routinely collected arealevel data, an appropriate choice in the earlystage of investigation of aetiological hypoth-eses; however these units may be inappropriateif they do not correspond to the actualgeographical distribution of the causal factors

linking social environment to health. If, forexample, social support is hypothesised to be akey mechanism then the interest might be inwhether or not residents receive social supportwithin the area they define as their neighbour-hood,6 whereas if access to health care wereconsidered more important, catchment areasfor local health service providers would be pre-ferred. Instead political boundaries providevery rough ecological profiles.26 These con-siderations also aVect the choice of area size touse. Debate has focused on the best choice ofarea size when area level measures are to beused as proxies for individual measures,

however, the choice of area size in contextualstudies is also deserving of thoughtfulconsideration.2730

Much of the discussion of the most appropri-ate geographical sub-unit for measuring neigh-bourhood social factors variables has focusedon homogeneity within areas.3133 A neighbour-hood need not be homogenous to aVect thelives of its inhabitants. In fact, complete homo-geneity within an area precludes the study of

contextual eVects altogether. Extremeheterogeneity may render measures of theimpact of neighbourhood averages, such asmedian household income, meaningless; in-deed a current discussion on the health eVectsof income inequality suggests that both theaverage and the spread of neighbourhoodsocial factors are worthy of examination.34

CHOICE OF AREA LEVEL SOCIAL VARIABLES

Neighbourhood level variables are either de-rived from individual level variables, such asmedian household income, or integral to theneighbourhood and only measurable at thatlevel,6 35 such as number of recreational facili-

ties.

8

Only two of the studies included integralvariables: level of services36 and number ofcommunity groups.37 The accessibility of cen-sus data may explain the paucity of research onintegral variables. Diez-Roux has noted thatderived variables are assumed to representintegral eVects,6 while Macintyre et al arguethat studies should focus directly on theintegral economic, cultural and political char-acteristics of neighbourhoods.8

Several composite indices have been devel-oped to handle highly correlated neighbour-hood level variables. The advantages of suchindices include statistical eYciency and a sim-ple presentation of results. Using many singlemeasures separately may lead to collinearity

and cumbersome or cluttered results, espe-cially when the intention is to reflect a singleunderlying concept such as neighbourhoodsocioeconomic status, rather than examiningthe unique contribution of each component.However, indices also have drawbacks: they arediYcult to construct and validate,38 39 and tendto mask variationthat is, two areas with thesame score may diVer in the values thatcontributed to that score. Indices have limitedexternal validity or utility across time40 andspace41 and, depending on their componentvariables and weights, may measure certainaspects of neighbourhoods, for example, struc-tural deprivation, better than others.

In the US, census variables used in contex-tual analyses have been derived from thedecennial censuses. Population counts andbasic demographic variables such as age, raceand gender are obtained for all residents, whilea one in six sample provides further detail onemployment, income, and education.42

CONTROLLING FOR INDIVIDUAL LEVEL

SOCIOECONOMIC STATUS

To understand the role of the social environ-ment in relation to health, neighbourhoodsocioeconomic factors and individual socio-economic status must be considered, as

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omitting either will result in incomplete modelbias. Without individual level information,neighbourhood level variables may act partiallyor entirely as proxies for individual attributesand a partition of the contribution of each tothe chosen health outcome is impossible.Without neighbourhood level measures, theimpact of individual characteristics may bemisunderstood.

Measurements of socioeconomic status are

not routine in the US, despite widespreadacceptance of the importance of these conceptsas determinants of health.43 Consequently, thechoice of socioeconomic variables in datacollection eVorts is driven by conveniencerather than theory. In the UK, occupationalclassification of social class is measured rou-tinely, most frequently by the British RegistrarGenerals Scale, and there is general agreementthat the scale captures some aspects of relativesocial position or class. The most commonlyused indicators of socioeconomic status in theUS are education, occupation and income, andthe relation of each of these to social class is amatter of some debate.44 45 One consensus that

emerges from the literature is that all three aresimple measures being used as proxies forcomplex concepts that we intuitively under-stand but cannot measure with accuracy, suchas social standing, access to resources, healthrelated attitudes, etc.

In 20 of the studies reviewed, individual levelsocial class or socioeconomic status wasmeasured by more than one variable, althoughnot all of these studies included more than onemeasure in any model. Correlation betweendiVerent measures of socioeconomic statusmakes the use of composite indices attractive(for example the 17 level index of individualsocioeconomic status used in the study by

Kleinschmidt et al of smoking behaviour46

).The disadvantages of using a composite indexare identical to those discussed above forneighbourhood level composites: it becomesimpossible to diVerentiate the independent andinteractive eVects of each component and valu-able information can be obscured. In the studyby OCampo et alof low birth weight, the eVectof neighbourhood per capita income on lowbirth weight is modified by individual healthinsurance status, and the eVect of neighbour-hood crime rates depends on individual educa-tion.47 These interesting interactions could nothave been observed if health insurance statusand education had been combined into a singleindex.

When only a single measure of individualsocioeconomic status is used, neighbourhoodvariables may be more likely to act as proxiesfor missing individual level information.

One study measured lifetime socioeconomicstatus as a combination of current, earlyadulthood and fathers occupational class.48

Interestingly, this was one of the two studieswhere neighbourhood eVects were statisticallynon-significant in models adjusted for indi-vidual socioeconomic status, suggesting thatneighbourhood characteristics may reflect life-time social circumstances or that lifetimeTa

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Reference

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199546

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Krieger,

199231*

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oking=1.4

fornon-workingclass

womeninnon-workingclassblockgroupv

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199537

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Reijneveld,

199866*

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116 Pickett, Pearl

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socioeconomic status is more strongly relatedto health than current circumstances.

CONTROLLING POTENTIAL CONFOUNDING

FACTORS

In studies of neighbourhood social factors andhealth outcomes, it is important for researchersto conceptualise the causal pathways by whichthey believe neighbourhood characteristicsaVect health. If causal pathways are believed to

involve neighbourhood associated diVerencesin health behaviours, such as smoking, thensuch behaviours are not potential confoundingvariables to be controlled, but componentcauses of a pathway that need to be ex-plored.49 50 As much of the literature on neigh-bourhood social factors and health outcomes isexploratory in nature, a variety of approachestowards adjusting for confounding factors havebeen taken, and the causal pathways thatunderlie hypotheses about the eVects of neigh-bourhood social factors are often not explicit.

When both a risk factor and a confoundingfactor are measured with error, the unmeas-ured variation in the confounding variable can

resonate and cause residual confoundingwith unpredictable eVects on estimates of rela-tive risk, unless the strength and direction ofthe correlation between risk factor and con-founder are known.51 It is probable that meas-urements of both neighbourhood and indi-vidual socioeconomic status contain error, andthat risk estimates for neighbourhood levelsocial factors are aVected by residual con-founding from measurement error of indi-vidual level socioeconomic status.

CHOICE OF ANALYTIC MODEL

Many of the multilevel studies we reviewedused single level linear and logistic regressionanalysis and Cox proportional hazards models

to estimate the impact of neighbourhoodfactors on health. In fact, the hierarchicalnature of such data, where individuals arenested within neighbourhoods, is more cor-rectly approached with multilevel models thataccount for this hierarchical clustering.52 Statis-tical models that assume that individuals areindependently sampled are unable to accountfor the intra-neighbourhood correlation thatarises from the fact that people from the sameneighbourhood will be more alike in unmeas-ured characteristics than people from diVerentneighbourhoods. This violation of the inde-pendence assumption can lead to incorrectestimation of the standard errors of model

parameters in non-hierarchical models and thepossibility of incorrect inference concerningthe eVect of the neighbourhood level character-istics. Estimation techniques for hierarchicalmodels for both discrete and continuousoutcomes have been developed, and computersoftware to implement them is now available instandard statistical packages.53 The importanceof using multilevel techniques is a matter ofcurrent debate.53 54 Ten of the 25 studiesreviewed used hierarchical models of somekind, all had publications dates between 19911998 (see table 1). The other 15, withpublication dates from 19831998, used single

level models. Although we noted an increase ofhierarchical modelling with time, five studiespublished in 1998 used single level models.One study that presented results from bothsingle level and multilevel analyses of the eVectof neighbourhood characteristics on domesticviolence provides an illustration of the poten-tial problems that may arise from an inappro-priate choice of models.37 The odds ratios (and95% confidence intervals) for risk of domesticviolence according to residence in a lowincome neighbourhood were 4.4 (1.1, 18.2) ina hierarchical model, and 4.9 (0.36, 66.7) in asingle level model. There is little change in theestimate of eVect but suYcient change in theestimate of the standard error to aVect signifi-cance tests.

ResultsResults of the 25 studies are presented in thelast column of table 1. The studies are groupedby the health outcome of interest to allow foreasier comparison.

MORTALITY STUDIES

Ten studies investigated the eVects of neigh-

bourhood social factors on mortality,48 5563although two of the studies were analyses of thesame sample,57 58 one study60 was conducted ona subset of another,59 and one study62 was alonger follow up of a previously analysedcohort.61 All of the studies focused on all causemortality (sometimes with separate analyses ofcause specific mortality) in both men andwomen, except for one that examined mortalityattributable to heart disease in women.60 Neigh-bourhood eVects are fairly consistent acrossstudies, with modest (RR less than 2.0) but sta-tistically significant increased risk of mortality inpoorer or more deprived neighbourhoods. Incontrast, Davey Smith and colleagues found

eV

ects of neighbourhood deprivation within cat-egories of lifetime socioeconomic status, but theoverall eVect of neighbourhood deprivation wasnot significant.48 Sloggett and Joshi found essen-tially no role for neighbourhood factors in alarge cohort with nine years of followup, with nosignificant area level eVects in men and a signifi-cant relative risk of only 1.02 in women.61 How-ever, after 13 years of follow up, significantneighbourhood eVects were found in both menand women.62

Three of these studies found the eVect ofneighbourhood to be modified by age55 60 63; inall three there was less impact of neighbourhood

KEY POINTS

x Attributing health disparities to neigh-bourhood social context requires the iso-lation of individual level socioeconomicinfluence.

x Neighbourhood has been operationallydefined in various ways in studies indeveloped countries, but few have con-formed to natural boundaries.

x

Findings of significant interactions sug-gest that neighbourhood context may dif-ferentially aVect the health of people.

Neighbourhood context and health outcome 117

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factors in older age groups, suggesting thatother factors related to survival may be moreimportant in older age groups. Haan et al andKaplan report separate analyses of the samesample.57 58 The greater magnitude of theneighbourhood eVect in Kaplans study may beattributable to the finer scale of the definedneighbourhoods (census tracts versus federalpoverty area).

Only one of the mortality studies used an

analytic model that accounted for the hierar-chical structure of the data, and its results areconsistent with the overall finding of modestlyincreased mortality risk.55

MORBIDITY STUDIES

Infant and child healthThe three studies that examined infant birthweight all found significant neighbourhoodeVects,25 47 62 but in all three the eVect wasmodest (RR less than 2.0). Neighbourhoodswith a high percentage of black residents werefound to protect against low birth weight in onestudy,25 while another reported multiple inter-actions between characteristics of mothers and

their neighbourhoods.

47

For example, theassociation of prenatal care with reducedincidence of low birth weight was stronger inareas with low unemployment, compared withareas with high unemployment, which suggeststhat prenatal care is less protective for womenliving in deprived neighbourhoods. In the onlystudy of childhood illness, Morgan and Chinnshowed that ACORN group, a classificationsystem for neighbourhood characteristics, wasassociated with bronchitis in the previous 12months, but asthma, all respiratory illnesses,doctor visits and hospital stays were not.64

Chronic disease among adultsTen studies investigated morbidity in adults,

including self rated health,4 65 66 long termdisability or illness,62 6568 cardiovascular riskfactors, symptoms or disease,4 31 56 69 and respi-ratory function or illness.4 56 65 Most studiesinvestigated multiple chronic conditions andoutcomes in order to capture a general conceptof adult health, whereas others focused on par-ticular outcomes (see for example stud-ies31 68 69).

Three of four studies on self rated healthfound significant neighbourhood eVects.4 65 67

Reijneveld found no significant neighbourhoodeVects on self rated poor health after adjust-ment of income, education and occupation.66

However, this study and the same authors

study of mental health (see below) may havelacked statistical power.Three studies found no significant neigh-

bourhood eVects on long term illness,65 func-tional limitations,67 and long term physicallimitations.66 Robert did find an eVect ofneighbourhood economic disadvantage (acomposite index) on number of chronicdiseases but no single neighbourhood variablehad a significant eVect.67 Shouls et al reportedthat neighbourhood deprivation was associatedwith increased risk of long term illness, andthat the neighbourhood eVect was stronger formen than women.68 Small but significant

neighbourhood eVects on long term limitingillness were reported in a more recent studyfrom the UK.62

Among the studies of coronary heart diseaseand its risk factors, Diez-Roux et al foundneighbourhood eVects on systolic blood pres-sure and serum cholesterol in all areas studied,but for heart disease only among women livingin predominantly white areas.69 Neighbour-hood deprivation scores were associated with

increased body mass index and prevalence ofangina and ischaemia among women, andincreased prevalence of angina among men in astudy population in Scotland.56 Jones andDuncan found increased reporting of heartdisease symptoms as neighbourhood depriva-tion increased among low and middle incomeadults, but the opposite among adults with highincomes.4 Neighbourhood eVects on hyper-tension among non-working class subjects werereported by Krieger.31

All three studies of adult respiratory functionreported at least one significant area leveleVect. Humphreys and Carr-Hill studied fiveneighbourhood characteristics and found that

only the percentage of people not owning a carwas a significant predictor.65 Jones and Duncanfound that urban neighbourhoods were associ-ated with poor respiratory functioning amongnon-smokers, while smokers had poor func-tioning regardless of neighbourhood urbanity.4

Davey Smith et alshowed significant trend testsfor increasing neighbourhood deprivation andrespiratory function and bronchitis.56

Studies of mental health

Only one study focused on mental health as anoutcome.70 No significant neighbourhood ef-fect persisted after adjustment for family size,occupation, and education. This study mayhave suVered from insuYcient statistical power

for two reasons: (1) there were only 22neighbourhoods (boroughs), limiting the abil-ity to detect between group diVerences17; and(2) the boroughs may have been too homog-enous, creating collinearity between individualand neighbourhood SES measures.

STUDIES OF HEALTH BEHAVIOURS

Seven studies investigated the eVects of neigh-bourhood social factors on health behavioursor attitudes.24 31 36 37 46 66 69 Five of these studieslooked at smoking behaviour as a primary out-come,31 36 46 66 69 one also examined alcohol anddietary intake,36 and one examined individualattitudes towards smoking, alcohol use and

dietary intake, rather than the behavioursthemselves.24 One study looked at reproductivehealth behaviours,31 and one study focused ondomestic violence.37

Four of the five papers that assessed theeVects of neighbourhood social factors onsmoking reported increased relative risks (RR)of smoking between 1.21.7 in neighbour-hoods with low socioeconomic status.31 46 66 69

The study by Karvonen and Rimpela in aFinnish population reported no significantrelations between neighbourhood and smok-ing,36 however this study focused on a sample ofadolescents, aged 1618 years, whereas the

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other four studies of smoking were in adults.Diez-Roux et al found that the eVect of neigh-bourhood social factors on smoking was modi-fied by both gender and race.69

Karvonen and Rimpela report several mod-est interactions between neighbourhood socio-economic status and gender in relation to ado-lescent health behaviours, despite finding noeVects for smoking.36 For example, the relativerisk for alcohol use was 1.35 among boys living

in areas with low employment status comparedwith boys living in areas with better employ-ment status, whereas the relative risk foralcohol use was 1.47 among girls living in areaswith high education status compared withareas with low education status. Further inter-actions between neighbourhood factors andschool type were reported, as well as equallycomplex results for the use of full fat milkproducts.

Curry et al studied attitudes towards healthbehaviours, hypothesising that neighbourhoodsocioeconomic status, as well as the prevalenceof health behaviours, will be related to socialtolerance and normative attitudes towards

health related behaviours.

24

Indeed, they foundneighbourhood eVects on attitudes towardssmoking and dietary fat consumption, but noton attitudes towards alcohol consumption.

OCampo and colleagues studied male part-ner violence towards women during the child-bearing year and report the largest magnitudeof neighbourhood eVects of all the studies weidentified, a relative risk of violence of 3.42 forhigh neighbourhood unemployment and of 4.4for low neighbourhood income.37 These greatermagnitudes may be attributable to the moredirect pathways that can be hypothesised tolead from stressful neighbourhood contextstowards violent behaviour, than can be conjec-tured for other health outcomes.

DiscussionWe have reviewed multilevel studies of neigh-bourhood socioeconomic context and health.In 23 of the 25 studies we identified, research-ers reported a statistically significant associ-ation between at least one neighbourhoodmeasure of socioeconomic status and health,controlling for individual socioeconomic sta-tus. The studies that found no associationincluded the only study of mental health70 andthe only study to measure lifetime rather thancurrent individual socioeconomic status.48 De-spite this apparent consistency across studies, adetailed appraisal of this literature suggests a

more complicated picture.An inclusion criterion for this review wasadjustment for individual level socioeconomicstatus. However, some studies adjusted for onlyone measure of individual socioeconomicstatus, whereas others adjusted for two ormore. Without adequate control of individualsocioeconomic status, neighbourhood leveleVects may act as proxies for unmeasuredaspects of individual socioeconomic status.27

Reijnevelds study of mental disorders illus-trates the eVects of controlling for multiplemeasures of individual socioeconomic status.70

In models adjusting for individual level educa-

tion or occupation, a statistically significantassociation was demonstrated between lowneighbourhood income and increased preva-lence of mental disorders. However, whenindividual level income was added to thesemodels, there was no statistically significantneighbourhood level eVect. In general, studiesadjusting for more than one individual levelmeasure of socioeconomic status found smallermeasures of association between neighbour-

hood level socioeconomic status and health.For example, Sloggett and Joshis study found amuch weaker association of neighbourhoodsocioeconomic status with all cause mortality,adjusting for three measures of individual levelsocioeconomic status,61 than the analyses ofHaan et als of the same association,57 each ofwhich were adjusted for only one measure ofindividual level socioeconomic status. On theother hand, the extent that neighbourhoodsocioeconomic status determines individualincome, education, and occupation, controllingfor individual socioeconomic status may re-move part of the contextual eVect.

We grouped studies by type of outcome, as

presented in table 1, to allow for easiercomparison of similar studies. However, as thisliterature is still fairly sparse, there are notenough replication studies using the samehealth outcomes, covariates, exposures andstudy designs to allow for more than a prelimi-nary guess of the magnitude of neighbourhoodeVects for particular health outcomes. Domes-tic violence during the childbearing yearshowed the strongest association with neigh-bourhood socioeconomic context.37 In general,risk ratios for low neighbourhood socioeco-nomic status and negative health behaviourswere consistent and modest, as were those formortality, but the impact of neighbourhoodcharacteristics on morbidity was more variable;

evidence for long term illness and disability wasweak,while evidence for respiratory function inadults was stronger.

It is possible, and even plausible, that somecharacteristics of neighbourhoods may be moreor less related to health outcomes than others,although many characteristics of neighbour-hoods are highly correlated. For instance aver-age neighbourhood income might be a betterpredictor of health status than the proportionof households suVering from overcrowding.The level at which variables are measured mayalso be important, for example, poverty at thecensus block group level might be morestrongly associated with health than poverty at

the county level. In the studies we review, it isdiYcult to compare the impact of diVerentneighbourhood characteristics or definitionsbecause of the heterogeneity in study designs.Studies that used indices of several neighbour-hood socioeconomic characteristics to rankneighbourhoods on a single dimension (usuallypoverty or deprivation) and those that usedfactor analysis to identify clusters of neigh-bourhood characteristics do not permit dis-crimination between the eVects of diVerentneighbourhood characteristics.

In studies with only a single individual levelSES variable, the neighbourhood level SES


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variables may be capturing unmeasured indi-vidual level variation in outcome,27 however wedo not believe that models that include onlyone measure of neighbourhood level socioeco-nomic status are equally suspect. Neighbour-hood level socioeconomic characteristics aremuch more highly correlated than individuallevel socioeconomic factors, so that mis-specifying the neighbourhood level eVect is lesslikely to occur. The choice of neighbourhood

level variables may be less critical than ensuringproper control for individual level socioeco-nomic status.

Neighbourhood socioeconomic contextmight aVect health either directly, if simply liv-ing in a deprived neighbourhood is deleteriousto health,7 or indirectly through such mecha-nisms as the availability and accessibility ofhealth services, healthy foods or recreationalfacilities, environmental pollution, normativeattitudes towards health, and social sup-port.6 8 1 7 Measures of neighbourhood socio-economic status can therefore be viewed asboth proxies for unmeasured mechanisms or asactual exposures in their own right, or both.

It is therefore important for researchers tobegin to be explicit about the causal pathwaysthey believe to be operating between neigh-bourhood socioeconomic context and health,and to consider how adjustment for factors onthe causal pathway may bias estimates ofneighbourhood factors. For example, adjustingfor smoking, which may be a consequence ofliving in a deprived neighbourhood, as well as acause of poor respiratory function, may weakenthe association between neighbourhood andhealth outcome. On the other hand, research-ers may be interested in how the associationbetween smoking and respiratory function ismodified by neighbourhood characteristics.

Most of the studies we reviewed were explora-tory in nature and did not specify the causalmechanisms linking the factors included intheir multivariate analyses, but this is clearly animportant next step for understanding therelation between neighbourhood and health.

British studies of neighbourhood eVectsstem from a larger movement examining socialinequalities and health that includes studies ofincome inequality, regional and rural-urbanvariation in health and social gradient research(see, for example, references3 4 10 33 65 7174). Pro-ponents and critics of this kind of research tendto be divided along sharply political lines. Inthe US, concern for social justice may be themotivation for some of this research but debateconcerning its implications has not reached thepolitical arena with any force. Epidemiologistsand others in public health often feel that iden-tifying social determinants of health may befruitless if the ability to change social structuresand inequalities lies outside of the public healthdomain. While these studies may provideammunition for political debate and drawattention to inequities in health, they also servethe purpose of identifying types of geographicalareas where traditional public health interven-tions, aimed at individual risk reduction, maybest be targeted and providing impetus for new

interventions when interesting associations arediscovered.

In the studies we review, relative risks aretypically modest. However, the populationattributable risk of living in neighbourhoodswith low socioeconomic status is likely to behigh, as such conditions are extremely preva-lent.

A potential problem with these studies is thattheir statistical power and findings depend on

there being people within each neighbourhoodwho are not typical of the neighbourhood, asheterogeneity is needed to distinguish betweenindividual level and neighbourhood level ef-fects. In other words, these studies are drivenby fish out of waterpeople who may beuncharacteristic of the neighbourhood inwhich they live in ways that researchers do notmeasure. Therefore, factors that may beassociated with being atypical might explainapparent neighbourhood eVects.

In addition, results derived from these smallnumbers of atypical residents may generalise toa small population group. For instance, Rob-erts found that while being black increased a

womans individual risk of having a lowbirthweight infant, living in a predominantlyblack neighbourhood was associated with adecreased risk.25 This means that black womenliving in predominantly white neighbourhoodsare particularly vulnerable. However, becausemore black women will live in predominantlyblack neighbourhoods than in predominantlywhite neighbourhoods, focusing preventionand policy eVorts on the small number ofatypical women would be ineYcient. Attentionto the prevalence of the exposure, as well asrelative risks, will ensure that preventive eVortsand public health policy will focus on thosepopulation sub-groups and geographical areaswhere most benefit can be expected.

It is clear from our review that investigationsof the role of neighbourhood level social factorson health are characteristic of preliminary,exploratory studies in epidemiology. Certainaspects of study design are in need of improve-ment before the field can advance. Firstly, defi-nitions of neighbourhood need to reflect actualneighbourhood boundaries more accurately.Secondly, careful delineation of theorisedcausal pathways will lead to more precise defi-nition and measurement of factors at theneighbourhood level that will allow tests ofcausal hypotheses. Qualitative information,such as that collected in sociological andethnographic research, can inform and guide

this process. Thirdly, if multilevel analyses ofneighbourhood level eVects are to provide use-ful information to guide public health policyand preventive programmes, data measuringimportant factors in real neighbourhoods needto be routinely collected and linked to healthoutcome data. As an example of what can beachieved in this manner, the city of Chicago hasdefined and collected information on commu-nity areas since the 1920s, giving rise to a richtradition of inquiry into the relations betweenneighbourhood factors and social outcomes(see for example, Sampson et al 75). Whendefined neighbourhoods are ecologically

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meaningful, constructs of social context aretheoretically based and examined for constructvalidity, and competing hypotheses are explic-itly defined and tested, we will better under-stand the eVect of neighbourhood context onhealth. We hope that this review will show whathas already been achieved and point the way tomore sophisticated studies of societal determi-nants of health.

We would like to thank Dr William Satariano, Dr Warren Win-kelstein, Dr Ralph Catalano, Dr Barbara Abrams, Dr SteveSelvin and Dr Irene Yen for encouragement and discussions, aswell as the helpful insights of our reviewers.

Funding: this work was supported by a grant from the Califor-nia Wellness Foundation.Conflicts of interest: none.

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