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Measuring the built environment: validity of a site survey instrument for use in urban settings
Health & Place 7 (2001) 283–292
Measuring the built environment: validity of a site survey instrument for use in urban settings Scott Weicha,*, Elizabeth Burtonb, Martin Blancharda, Martin Princec, Kerry Sprostond, Bob Erensd a
Department of Psychiatry and Behavioural Sciences, Royal Free and University College Medical School, Royal Free Campus, Rowland Hill Street, London NW3 2PF, UK b Oxford Centre for Sustainable Development, School of Architecture, Oxford Brookes University, Gipsy Lane, Headington, Oxford OX3 0BP, UK c Section of Epidemiology, Institute of Psychiatry, De Crespigny Park, London SE5 8AF, UK d National Centre for Social Research, 35 Northampton Square, London EC1 V 0AX, UK Received 27 July 2000; received in revised form 17 January 2001; accepted 10 May 2001
Abstract There are few reliable measures of place with which to study the effects of socio-economic context on health. We report on the development and inter-rater reliability of a 27-item observer-rated built environment site survey checklist (BESSC). Across eleven ‘housing areas’ (defined as areas of homogeneity in housing form) and two raters, kappa coefficients were X0.5 for fifteen categorical items, and intra-class correlation coefficients exceeded 0.6 for a further three continuous measures. Ratings on several BESSC items were associated to a statistically significant degree with the prevalence of depression and residents’ dissatisfaction with ‘their area as a place to live’. BESSC items may prove to be valuable descriptors of the urban built environment in future studies. r 2001 Elsevier Science Ltd. All rights reserved. Keywords: Built environment; Context; Measurement; Reliability
Introduction As the evidence for inequalities in morbidity and mortality by occupational social class and wealth has become irrefutable (Acheson, 1998; Marmot and Wilkinson, 1999), attention has turned to geographical variations in health, and to the effects of context (MacIntyre, 1997; Ecob and MacIntyre, 2000). Despite the importance currently attached to building ‘healthy communities’ (Department of Health, 1999); National Strategy for Neighbourhood Renewal, 2000), it is still not known which aspects of the social, economic and physical environments have the greatest effects on health (Sloggett and Joshi, 1994; Lynch et al., 2000). This is *Corresponding author. Tel.: +44-20-7830-2350; fax: +4420-7830-2808. E-mail address: [email protected] (S. Weich).
partly because most previous research on the geographies of health has been based on studies of the aggregated socio-economic characteristics of people living in particular areas (measures of ‘social composition’), rather than ‘contextual’ characteristics of the places where people live (MacIntyre, 1997; Ecob and MacIntyre, 2000). There is an extensive literature on the associations between poor housing and worse physical and mental health (Wilkinson, 1999; Dunn, 2000), but most of this is based on cross-sectional studies, which are unable to distinguish between causal associations and those due to social selection or recall bias. Furthermore, most previous research into the effects of housing on health has been concerned with tenure (Lewis et al., 1998; Weich and Lewis, 1998), and the effects of structural problems, such as damp or infestation (Platt et al., 1990; Hopton and Hunt, 1996; Smith and Mallinson, 1997;
1353-8292/01/$ - see front matter r 2001 Elsevier Science Ltd. All rights reserved. PII: S 1 3 5 3 - 8 2 9 2 ( 0 1 ) 0 0 0 1 9 - 3
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Acheson, 1998; Weich and Lewis, 1998; Marsh et al., 2000). There have been very few studies of the associations of the effects of the wider environment outside the home. One exception was a survey of a random sample of residents in West Central Scotland, which identified three ‘psychosocial benefits’ associated with the home: the home as haven, as a locus of autonomy and as a source of status (Kearns et al., 2000). Statistically significant associations were found between all three dimensions and respondents’ perceptions of the ‘area environment’ (such as litter, vandalism and crime), and the ‘people in the area’ (including noise, other types of disturbance, and ‘neighbourhood reputation’). However, only the latter remained statistically significant after adjusting for housing tenure and problems associated with the dwellings themselves, such as damp. There is also evidence that those living in urban areas experience worse physical and mental health than those living in rural or suburban areas (Lewis and Booth, 1994; Meltzer et al., 1995; Dorling, 1997). The mechanisms underlying this association remain poorly understood, although there is now little support for the oncepopular notion of geographical drift (Lewis et al., 1992; Verheij, 1996). It is not yet known, however, to what extent higher rates of morbidity and mortality in urban areas are explained by individual-level socio-economic deprivation, such as low income or unemployment (Sloggett and Joshi, 1994; Dunn, 2000). One important aspect of life in urban areas is the built environment. Defined broadly, the built environment includes many characteristics of places that cannot be reduced to the characteristics of the people who live there, such as housing form, roads and footpaths, transport networks, shops, markets, parks and other public amenities, and the disposition of public space. The built environment is likely to affect important aspects of the environment in which people live in both direct ways, such as effects on traffic, noise and air pollution, and in less tangible ways, by influencing the sense of community and ‘social capital’ in an area (Dunn, 2000). Evaluating associations between the built environment and health is therefore highly challenging, particularly when attempting to elucidate the mechanisms that might link these. Two previous studies of the effects of urban regeneration on mental health assessed the impact of improvements in the built environment that were intended to increase security and community participation, even though both were primarily ‘bricks and mortar’ interventions. Although both treated urban regeneration as a ‘black box’ intervention, both found that improvements in the built environment were associated with lower levels of anxiety and depression (Halpern, 1995; Dalgard and Tambs, 1997). Both studies were, however, limited by measures of the built environment that relied on
residents’ perceptions, and may therefore have been prone to recall bias. The dearth of empirical research into the effects of specific features of the built environment on health may be partly due to the absence of reliable and valid ‘objective’ measures. One notable exception was the study of young married women living on a housing estate in south–east London (Birtchnell et al., 1988). In this study, Birtchnell and his colleagues rated several aspects of the built environment including housing form, density, accessibility, entrance type and position, and control over the ‘buffer zone’ between private and public space, using a 15-item scale of ‘design variables’. Although this scale was based on previously published research, the authors did not report its psychometric properties. Birtchnell and his colleagues (1988) found that, compared with non-depressed controls, depressed women were significantly more likely to be living in blocks with raised walkways than in brick or concrete houses, or in tower blocks. The present study was conducted prior to an evaluation of the effects of an urban regeneration programme on the mental health of local residents in an electoral ward in north London. The main initial thrust of the regeneration programme was external refurbishment, and improving the quality of the built environment. We hypothesised that improvements in the built environment would be associated with a reduction in the prevalence of depression. The aim of the present study were twofold; first, to evaluate the psychometric properties of a set of ‘objective’ measures of the built environment, and second, to validate this by evaluating associations with the prevalence of depression, among residents in two inner city electoral wards in north London.
Methods The present study was conducted as a preliminary to a prospective cohort study, comparing changes in mental health over three years among individuals living in two electoral wards in north London. One of these wards was the site of a programme of improvements to the built environment, as part of the Capital Challenge scheme, while the other was selected as a control, for the purposes of evaluation. The control ward was chosen on the basis of its similarity to the intervention ward in socio-demographic composition and the character of its housing, using a variety of sources. This ward was also chosen because there was no similar urban regeneration programme underway at the time. The estimated populations of the experimental and control wards in 1999 were 6260 and 9549, respectively. Respondents to the main survey were selected in two stages using random probability sampling methods. The
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postcode address file (PAF) was used as the sampling frame for selecting about 1300 addresses within each ward. All addresses that were residential and occupied were eligible, and up to 2 adults (aged 16+) were sampled at random within each household using a Kish grid technique. Once selected, no substitutions were allowed. The household response rate was 64%. Eightythree percent of selected individuals within participating households agreed to take part, resulting in a survey sample of 1902. Housing areas Each of the two study wards was sub-divided into discrete housing areas. This was done a priori by one of the authors (EB), a trained architect, prior to collecting any other data. A housing area was defined as a geographically bounded area in which the majority of the housing is homogeneous in form and character. There was considerable variation in the number of dwellings within each housing area, which ranged from a tower block to streets of terraced houses. Thirty-three housing areas were enumerated in the experimental ward, and 53 in the control ward. Built environment site survey The built environment site survey checklist (BESSC) comprised a standardised list of items to be rated. Items included the predominant form, height and age of housing, number of dwellings and type of access, provision of gardens, use of public space, amount of derelict land, security, and accessibility of local shops and amenities (see Appendix A). Twenty-five out of 27 items in the BESSC had fixed categorical responses. The two remaining items required the researcher to rank features of the built environment (e.g. the proportion of space used in particular ways), and to estimate the distance from the centre of the ‘housing area’ to a range of amenities (e.g. bus stop). Checklist items were drawn from several sources, including three national housing surveys, namely the Housing Attitudes Survey (Department of the Environment, 1994), Housing in England (Office for National Statistics, 1997), and British Social Attitudes (SCPR, 1997). Other sources of items included texts on urban design (Bentley et al., 1985; Coleman, 1985), and published studies in this field (Birtchnell et al., 1988; Perkins et al., 1992). The BESSC was piloted and amended before final use. Data collection Each housing area was allocated an identifying number. Every third area in the experimental ward was selected for the reliability study. These 11 areas were
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rated independently by two researchers, using BESSC. Both researchers were postgraduate students in urban design with backgrounds in architecture. One of the researchers also used the BESSC to rate the other 75 housing areas across the two wards. The researchers were briefed prior to data collection by one of the authors (EB), to ensure consistency in their understanding of each of the items on the checklist, and to clarify any misunderstandings. Briefing took approximately 3 h. Within each housing area, the researchers were instructed to locate and mark the following onto maps: bus stops, GP surgeries, food stores, newsagents, pubs and schools. Data were collected in April and May, 1999. Prevalence of depression The prevalence of depression was assessed using the Center for Epidemiologic Studies Depression scale (CES-D) (Radloff, 1977; Roberts and Vernon, 1983; Beekman et al., 1997). This brief, 20-item self-report measure was developed as a measure for identifying probable cases of clinically significant depression in epidemiological surveys. Each item includes four response categories, and is scored using a Likert scale (0–3). Those scoring 16 or more (out of a possible score of 60) were classified as cases, in keeping with previous studies (Frerichs et al., 1981; Harlow et al., 1999). Although results are presented here for ‘cases’ of depression, there was no reason to expect that using CES-D score as a continuous variable would lead to different results (Anderson et al., 1993). Respondent attitudes Survey respondents were asked to rate their satisfaction with ‘‘the area as a place to live’’. Responses were coded on a five-point scale, ranging from ‘very satisfied’ to ‘very dissatisfied’. These were then dichotomised, with one indicating ‘fairly dissatisfied’ or ‘very dissatisfied’, and 0 otherwise. Respondents were not given any advice about the geographical boundaries of their area when answering this question. Statistical analysis All analyses were undertaken using Stata (Stata Corporation, 1999). For the BESSC reliability study, inter-rater reliability was assessed using the kappa and weighted kappa statistics for categorical variables and item rankings, and intra-class correlation coefficients for continuous measures. The kappa statistic is the most widely used measure of inter-rater reliability, and reflects the difference between the rate of agreement between two raters and that expected by chance. Where there are more than two ordered categories, the weighted kappa statistic reflects the degree of difference between raters
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(in terms of the number of categories between their respective observations), rather than simply whether or not they agree (Armitage and Berry, 1994). BESSC items with good inter-rater reliability or better (kappa X0.5) were included in subsequent analyses. These items are shown in the Appendix B. Associations between responses to BESSC items and (i) the prevalence of depression, and (ii) dissatisfaction with the area as a place to live, were assessed using odds ratios (with 95% confidence intervals), estimated by means of logistic regression. These analyses were undertaken using the survey commands within Stata (Stata Corporation, 1999), which adjusts standard errors for the stratification of the sample by electoral ward, and the clustering within housing areas and households (Huber, 1981). Data were weighted by household size, in order to adjust point estimates for the probability of selection.
Results Inter-rater reliability of BESSC items Table 1 shows the degree of inter-rater reliability for the full list of categorical items in BESSC, across the 11
housing areas surveyed for the reliability study. Low kappa coefficients were found when comparing the rankings used to rate the division of space within each housing area (BESSC item 7, Appendix A), the highest of which was 0.46 (SE 0.23) (p ¼ 0:02), for shared garden/open space. Table 2 shows the intra-class correlation coefficients for the estimated distances from the centre of the housing area to the nearest amenity of each type (BESSC item 19). Overall, fifteen out of 25 categorical BESSC items had kappa coefficients of X0.50.
Associations with the prevalence of depression and resident satisfaction The prevalence of depression was 39.0%, as defined by a cut-off of 15/16 on the CES-D. This rate did not vary to a statistically significant degree between the two study wards (w2 ¼ 0:51; df ¼ 1; p ¼ 0:47). Statistically significant associations were found between the prevalence of depression and five of the fifteen BESSC items with satisfactory inter-rater reliability. After adjusting for the clustering of respondents within housing areas (and wards), statistically significant associations were
Table 1 Inter-rater reliability of the site survey items, showing the number of response categories, agreement between raters, and kappa statistic (with standard error), for each item. Items with kappa values X0.50 are shown in bold Item (number: see Appendix A)
Number of categories
% agreement
Kappa (SE)
Housing form Number of storeys of buildings Type of access to dwellings No. of dwellings per entrance No. of dwellings in housing area Age of housing Number of trees in public domain Nature of space outside dwellings Private gardens: proportion Private balconies: proportion Shared recreational space Number of vehicular entrances Number of pedestrian entrances Entrances visible from roads Entrances visible from footpaths Parking arrangements Number of children’s play areas Footpaths overlooked Open spaces overlooked Disused buildings Derelict land Evidence of vandalism Evidence of graffiti Territorial functioning Neighbourhood watch signs
2 5 3 8 6 5 5 3 3 3 2 5 5 5 5 5 5 3 3 2 2 3 3 3 2
81.8 86.4 81.8 87.3 86.4 84.9 84.9 77.8 81.8 77.3 100 86.4 84.1 77.3 68.2 36.4 84.9 81.8 45.5 90.9 80.0 36.4 90.9 45.5 90.9
0.54 (0.30) 0.57 (0.20)a 0.72 (0.21) 0.64 (0.21)a 0.67 (0.22)a 0.64 (0.20)a 0.65 (0.22)a 0.61 (0.22) 0.65 (0.26) 0.52 (0.25) 1.00 (0.24) 0.48 (0.20)a 0.65 (0.22)a 0.50 (0.20)a 0.04 (0.18)a 0.21 (0.13) 0.44 (0.20)a 0.05 (0.14) 0.26 (0.17) 0.62 (0.28) Fb 0.07 (0.11) 0.76 (0.24) 0.23 (0.13) 0.0 (0.0)
a b
weighted kappa. kappa statistic could not be calculated because of empty cells.
p 0.04 0.002 0.0003 0.001 0.001 0.0008 0.002 0.003 0.006 0.02 o0.0001 0.008 0.002 0.006 0.42 0.05 0.01 0.63 0.06 0.01 Fb 0.26 0.001 0.04 0.50
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found between the prevalence of depression and living in housing areas where (i) most properties had deck access; (ii) properties were mainly built after 1940; (iii) fewer than one-quarter of homes had a private garden; (iv) there was a shared recreational space; and (v) many patches of graffiti were observed (Table 3). No statistically significant associations were found between the prevalence of depression and the distance from the centre of the housing area to the nearest bus stop, public house or school. A statistically significant difference was found between the two study wards in the proportion of respondents who were dissatisfied with their area ‘as a place to live’ (w2 ¼ 6:94; df ¼ 1; p ¼ 0:008). More of those living in the experimental ward (14.4%) than in the control ward (10.3%) were dissatisfied in this way. After adjusting for the clustering of respondents within housing areas (and wards), the pattern of associations with BESSC items almost identical to that found
Table 2 Intra-class correlation (icc) coefficients (with standard errors) for ratings of distance from centre of housing area to nearest amenities, for two raters Amenity
icc coefficient (SE)
p
Nearest Nearest Nearest Nearest Nearest
0.64 0.07 0.28 0.94 0.93
0.01 0.41 0.18 o0.0001 o0.0001
bus stop GP surgery newsagent public house school
(0.18) (0.31) (0.29) (0.03) (0.03)
between the latter and the prevalence of depression. Statistically significant associations were found between dissatisfaction with their area ‘as a place to live’ and all but one of the BESSC items that were associated with the prevalence of depression to a statistically significant degree. The one difference in associations with these two outcomes was the proportion of homes with private gardens, for which the association with ‘dissatisfaction’ did not reach statistical significance (Table 4). No statistically significant associations were found between dissatisfaction with the area as a place to live and the distance from the centre of the housing area to the nearest bus stop, public house or school.
Discussion It is still not known whether, or how, the built environment affects health, independent of individuals’ material circumstances. The present study represents a preliminary attempt to develop a set of reliable measures of the characteristics of the built environment in urban settings, with which to further address these questions. There was relatively little published empirical evidence to guide the choice of items, and consequently we opted for items with the greatest face validity, and those that were likely to be of acceptable reliability. The majority of items in our checklist were of satisfactory inter-rater reliability. Of the 25 items in Table 1, kappa coefficients for only 10 were below 0.5, a value that reflects moderate to good inter-rater reliability (Stata Corporation, 1999). Eleven items had kappa
Table 3 Odds ratios (95% CI) for bivariate associations between the prevalence of depression and BESSC items with satisfactory inter-rater reliability (X0.50) BESSC item
OR (95% CI)
p
Non-traditional housing form (v traditional) Most buildings >3 storeys (vp3 storeys) Deck access (v other types of access) >5 dwellings per entrance (vp5) o50 dwellings in housing area (vX50) Properties built 1940–1969 (v pre-1940) Properties built 1970 or later (v pre-1940) o5 trees in public domain (vX5) Non-private space outside properties (v private) o 14 homes with private gardens ðvX14Þ o 14 homes with private balconies ðvX14Þ No shared recreational space (v any) 3–9 pedestrian entrances to housing area ðvp2Þ X10 pedestrian entrances to housing area ðvp2Þ Building entrances visible from roads (v none) Disused buildings (v none) Some patches of graffiti (v none) Many patches of graffiti (v none)
1.24 1.29 1.57 0.87 0.89 1.88 2.36 1.18 1.15 1.75 0.81 0.52 0.81 1.02 0.73 1.15 1.28 2.12
0.41 0.22 0.03 0.46 0.51 0.009 o0.001 0.43 0.65 0.03 0.35 0.008 0.37 0.90 0.14 0.36 0.32 0.006
(0.73–2.10) (0.85–1.95) (1.05–2.34) (0.52–1.35) (0.61–1.28) (1.18–3.00) (1.53–3.65) (0.77–1.81) (0.63–2.12) (1.07–2.85) (0.52–1.27) (0.32–0.84) (0.51–1.29) (0.74–1.41) (0.49–1.11) (0.84–1.58) (0.79–2.09) (1.25–3.59)
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Table 4 Odds ratios (95% CI) for bivariate associations between dissatisfaction with ‘the area as a place to live’ and BESSC items with satisfactory inter-rater reliability (X0.50) BESSC item
OR (95% CI)
p
Non-traditional housing form (v traditional) Most buildings >3 storeys (vp3 storeys) Deck access (v other types of access) >5 dwellings per entrance (vp5) o50 dwellings in housing area (vX50) Properties built 1940–1969 (v pre-1940) Properties built 1970 or later (v pre-1940) o5 trees in public domain (vX5) Non-private space outside properties (v private) o 14 homes with private gardens ðvX14Þ o 14 homes with private balconies ðvX14Þ No shared recreational space (v any) 3–9 pedestrian entrances to housing area ðvp2Þ X10 pedestrian entrances to housing area ðvp2Þ Building entrances visible from roads (v none) Disused buildings (v none) Some patches of graffiti (v none) Many patches of graffiti (v none)
1.52 0.83 2.90 0.70 1.29 8.56 6.51 0.89 1.29 2.26 0.58 0.23 0.85 1.22 0.68 0.87 1.28 2.12
0.28 0.60 0.004 0.39 0.48 o0.001 o0.001 0.77 0.53 0.16 0.19 0.002 0.71 0.58 0.38 0.68 0.32 0.006
coefficients X0.6 (indicative of ‘substantial’ reliability), of which one (presence of any shared recreational space within the housing area) had a kappa value of 1.0. Kappa coefficients were lower where researchers were required to rank the proportion of space within housing areas occupied by different environmental features. Intra-class coefficients for the distance between the centre of the housing area and different amenities (using maps) varied from the very high (>0.9) for the nearest public house and school, respectively, to the very low (o0.1) for the nearest GP surgery. There was evidence of statistically significant associations between five measures of the built environment (all of which had kappa values of X0.50) and the prevalence of depression. In particular, those who were identified as cases of depression were more likely to be living in housing areas characterised by newer (post-1940) properties, with deck access but few private gardens, and with shared (public) recreational space(s) and evidence of many patches of graffiti. Together, these items would appear to describe the type of inner city, local authority-owned housing estate with which drug misuse and crime are often associated. Of these, only the proportion of homes without gardens was not associated with residents’ dissatisfaction with their own area ‘as a place to live’ to a statistically significant degree. There was no evidence of any statistically significant associations between depression or dissatisfaction and distance to any of the three amenities whose location was identified consistently in the reliability study, namely the nearest, bus stop, school or public house. The
(0.71–3.27) (0.41–1.70) (1.42–5.91) (0.30–1.59) (0.63–2.63) (3.63–20.18) (2.89–14.66) (0.41–1.95) (0.58–2.86) (0.73–7.05) (0.26–1.31) (0.09–0.57) (0.35–2.04) (0.59–2.53) (0.29–1.62) (0.46–1.67) (0.79–2.09) (1.25–3.59)
pattern of associations with the prevalence of depression, in particular, was consistent with the results of Birtchnell et al. (1988), although the latter study was restricted to women. Taken as a whole, our findings provide support for the reliability of (at least) fifteen items, and for the concurrent validity of five items from the BESSC. However, the sample size for the reliability study was relatively small, comprising just 11 housing areas, and standard errors were large. Failure to find statistically significant inter-rater reliability for some of items may therefore have been due to type II error. Nevertheless, rates of agreement were high, exceeding 70% for 21 out of the 25 categorical items shown in Table 1. Estimates of inter-rater reliability reached statistical significance at the level of po0:01 for 15 out of the 35 items analysed. It is possible that failure to find more statistically significant associations with the prevalence of depression, or with dissatisfaction with the area ‘as a place to live’ were also due to the methodological limitations of the study. Both study wards, though not contiguous, were located within the same London Borough, and the homogeneity of housing areas on many of the BESSC items may therefore have precluded the emergence of strong associations with these two outcomes. Indeed, the control ward was chosen specifically because it resembled the experimental ward in the character of its housing stock. One strength of this study was the a priori definition of housing area boundaries. Although there is evidence that architects’ judgements, particularly in terms of
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aesthetics, differ from those of the general population (Devlin and Nasar, 1989; Halpern, 1995), the purpose of this study was to develop and evaluate an ‘objective’ measure of the built environment. Although there has been a great deal of research into the effects of housing on health, this has been based almost exclusively on the characteristics of individual homes, housing tenure, or residents’ satisfaction (Kearns et al., 2000). While our approach may be criticised for not incorporating residents’ views about the boundaries of housing areas, it was notable that we found associations between ratings of researcher-defined housing areas and residents’ satisfaction without providing the latter with any advice about the geographical boundaries of ‘their area’. One important limitation is that these findings, and the BESSC itself, may not be generalisable to other urban areas, and are unlikely to be applicable in suburban or rural settings. In the first instance, further research is needed to validate this measure in other urban settings. Conclusions Our findings suggest that it is both possible and feasible to rate the characteristics of the built environment in an urban setting independent of residents’ subjective perceptions. Most items, excluding those that required researchers to rank the use of land, showed at least moderate inter-rater reliability. Although further work is now required to refine and validate the measures described in this paper, in other independent areas, they may well prove useful in the further study of the effects of the built environment on physical and mental health. Further research is also needed to determine the possible mechanisms underlying associations between living in areas characterised by (for example) post-war housing and higher rates of depression.
Acknowledgements We would like to thank Ken Brodie and Juliet Matthews for collecting the site survey data, and Haroula Baladimou for collating it. We are also grateful to David Walker, of the London Borough of Camden, for providing us with demographic data about the two study wards.
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Non-traditional (Tower block/Slab block/Perimeter block/Cluster/Ribbon/Other) 2. How many storeys high are the majority of the buildings? 1 2 3,4 5–9 10+ 3. What type of access do most dwellings have? Direct from Deck access Internal corridor street or garden or stairwell 4. What is the typical number of dwellings per main entrance? (Main entrance defined as first door or gate into building) 1 2 3 4 5 6–9 10–19 20+ 5. Roughly how many dwellings are there in the housing area? 1–5 5–9 10–19 20–49 50–99 100+ 6. Approximately when was the housing built? Pre-1914 1914–1939 1940–1969 1970–1989 1990+ Space around the buildings 7. How is the open space divided up? (Rank the following, assigning 1 for the greatest proportion of space) Derelict/unused land Roads/footpaths Private gardens Shared garden/recreation space Parking areas 8. How many trees are visible in the public domain? None o5 approximately 5–9 approximately 10–19 20+ 9. What is the nature of the space immediately outside most front doors (i.e. doors to individual dwellings)? Private (Garden/Terrace/Corridor or stairwell) Shared (Garden/Terrace/Corridor or stairwell) Public (Public area/ Footpath/ External or semi-external corridor) 10. Approximately what proportion of dwellings have their own private garden space? Less than 14 Between 14 and 12 More than 12
Appendix A. Built Environment Site Survey Checklist (BESSC)
11. Approximately what proportion of dwellings have their own private balcony or terrace? Less than 14 Between 14 and 12 More than 12
Predominant characteristics of buildings 1. What is the predominant housing form? Traditional (Detached/Semi-detached/Terraced)
12. Does the housing area include any shared garden or other recreational open space? No Yes
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13. Roughly how many vehicular entrances are there into this housing area? 1 2 3,4 5–9 10+ 14. Roughly how many pedestrian entrances are there into this housing area? 1 2 3,4 5–9 10+ 15. On the whole, how many main entrances to buildings are visible from the main vehicular routes through the area? (main entrance defined as first door or gate into buildings) All Most Some Hardly any None 16. On the whole, how many main entrances to buildings are visible from the main pedestrian routes through the area? (main entrance defined as first door or gate into buildings) All Most Some Hardly any None 17. What are the parking arrangements (mainly)? None Offstreet only Predominantly private parking Predominantly public courts Mixed Facilities and accessibility 18. How many children’s play areas does the housing area have? None 1 2 3 4+ 19. From about the mid-point of the development, roughly how far is it to the following? (can calculate from map) Nearest bus stop Nearest GP surgery Nearest newsagent Nearest pub Nearest school
24. Are there signs of vandalism (e.g. broken telephone boxes, broken windows, damaged equipment) within the housing area? No Some signs Many signs 25. Are there patches of graffiti in the housing area? No Some signs Many signs 26. Are there signs of territorial functioning in the area? (e.g. decorated gardens/balconies, nameplates, window boxes) No Some signs Many signs 27. Are there any neighbourhood watch signs? No Yes
Appendix B. Items with satisfactory inter-rater reliability (kappa X0.50), and codings used to test for associations with the prevalence of common mental disorders. Numbers in brackets refer to full site survey checklist, BESSC, shown in Appendix A 1. Housing form (BESSC 1) What is the predominant housing form? 1=Traditional, 2=Non-traditional 2. Number of storeys (BESSC 2) How many storeys high are the majority of the buildings? 1=3 or fewer, 2=More than 3 3. Type of access (BESSC 3) What type of access do most dwellings have? 1=Access from street, garden, internal corridor or stairwell, 2=Deck access
Safety and security 20. Roughly what proportion of the footpaths/pavements through the development/area are overlooked by dwelling windows (i.e. windows no more than 10–15 m away)? Less than 14 Between 14 and 12 More than 12
4. Number of dwellings per entrance (BESSC 4) What is the typical number of dwellings per main entrance? 1=5 or fewer, 2=More than 5
21. On the whole, are the open spaces/play areas overlooked by dwelling windows? None Some Mostly
5. Number of dwellings in housing area (BESSC 5) Roughly how many dwellings are there in the housing area? 1=49 or fewer, 2=50 or more
22. Are any disused buildings (not vacant dwellings) evident in the housing area? No Yes
6. Age of housing (BESSC 6) Approximately when was the housing built? 1=pre-1940, 2=1940–1969, 3=1970 or later
23. How much of the land within the housing area seems to be derelict or unused? Less than 14 Between 14 and 12 More than 12
7. Trees (BESSC 8) How many trees are visible in the public domain? 1=5 or more, 2=Fewer than 5
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8. Space outside dwellings (BESSC 9) What is the nature of the space immediately outside most front doors? 1=Private, 2=Non-private 9. Private garden (BESSC 10) Approximately what proportion of dwellings have their own private garden space? 1= 14 or more, 2=Less than 14 10. Private balcony or terrace (BESSC 11) Approximately what proportion of dwellings have their own private balcony or terrace? 1=14 or more, 2=Less than 14 11. Shared recreational space (BESSC 12) Does the housing area include any shared garden or other recreational open space? 1=Yes, 2=No 12. Number of pedestrian entrances (BESSC 14) Roughly how many pedestrian entrances are there into this housing area? 1=Fewer than 3, 2=3–9, 4=10 or more 13. Entrances visible from road? (BESSC 15) How many entrances to buildings are visible from the main vehicular routes through the area? 1=Any, 2=None 14. Disused buildings (BESSC 22) Are any disused buildings (not vacant dwellings) evident in the housing area? 1=No, 2=Yes 15. Graffiti (BESSC 25) Are there patches of graffiti in the housing area? 1=No, 2=Some, 3=Many
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Radloff, L.S., 1977. The CES-D scale: a self-report depression scale for research in the general population. Applied Psychological Measurement 1, 385–401. Roberts, R.E., Vernon, S.W., 1983. The Center for Epidemiologic Studies Depression scale: its use in a community sample. American Journal of Psychiatry 140, 41–46. SCPR, 1997. British Social Attitudes: The Fourteenth Report. Ashgate Publishing: Aldershot. Sloggett, A., Joshi, H., 1994. Higher mortality in deprived areas: community or personal disadvantage? British Medical Journal 309, 1470–1474. Smith, S., Mallinson, S., 1997. Housing for health in a postwelfare state. Housing Studies 12, 173–199. Stata Corporation, 1999. Stata Statistical Software: Release 6.0. Stata Corporation: College Station, Texas. Verheij, R.A., 1996. Explaining urban-rural variations in health: a review of interactions between individual and environment. Social Science and Medicine 42, 923–935. Weich, S., Lewis, G., 1998. Material standard of living, social class and the prevalence of the common mental disorders in Great Britain. Journal of Epidemiology and Community Health 52, 8–14. Wilkinson, D., 1999. Poor Housing and Ill Health: A Summary of Research Evidence. The Scottish Office, Central Research Unit, Edinburgh.
Measuring the built environment: validity of a site survey instrument for use in urban settings Scott Weicha,*, Elizabeth Burtonb, Martin Blancharda, Martin Princec, Kerry Sprostond, Bob Erensd a
Department of Psychiatry and Behavioural Sciences, Royal Free and University College Medical School, Royal Free Campus, Rowland Hill Street, London NW3 2PF, UK b Oxford Centre for Sustainable Development, School of Architecture, Oxford Brookes University, Gipsy Lane, Headington, Oxford OX3 0BP, UK c Section of Epidemiology, Institute of Psychiatry, De Crespigny Park, London SE5 8AF, UK d National Centre for Social Research, 35 Northampton Square, London EC1 V 0AX, UK Received 27 July 2000; received in revised form 17 January 2001; accepted 10 May 2001
Abstract There are few reliable measures of place with which to study the effects of socio-economic context on health. We report on the development and inter-rater reliability of a 27-item observer-rated built environment site survey checklist (BESSC). Across eleven ‘housing areas’ (defined as areas of homogeneity in housing form) and two raters, kappa coefficients were X0.5 for fifteen categorical items, and intra-class correlation coefficients exceeded 0.6 for a further three continuous measures. Ratings on several BESSC items were associated to a statistically significant degree with the prevalence of depression and residents’ dissatisfaction with ‘their area as a place to live’. BESSC items may prove to be valuable descriptors of the urban built environment in future studies. r 2001 Elsevier Science Ltd. All rights reserved. Keywords: Built environment; Context; Measurement; Reliability
Introduction As the evidence for inequalities in morbidity and mortality by occupational social class and wealth has become irrefutable (Acheson, 1998; Marmot and Wilkinson, 1999), attention has turned to geographical variations in health, and to the effects of context (MacIntyre, 1997; Ecob and MacIntyre, 2000). Despite the importance currently attached to building ‘healthy communities’ (Department of Health, 1999); National Strategy for Neighbourhood Renewal, 2000), it is still not known which aspects of the social, economic and physical environments have the greatest effects on health (Sloggett and Joshi, 1994; Lynch et al., 2000). This is *Corresponding author. Tel.: +44-20-7830-2350; fax: +4420-7830-2808. E-mail address: [email protected] (S. Weich).
partly because most previous research on the geographies of health has been based on studies of the aggregated socio-economic characteristics of people living in particular areas (measures of ‘social composition’), rather than ‘contextual’ characteristics of the places where people live (MacIntyre, 1997; Ecob and MacIntyre, 2000). There is an extensive literature on the associations between poor housing and worse physical and mental health (Wilkinson, 1999; Dunn, 2000), but most of this is based on cross-sectional studies, which are unable to distinguish between causal associations and those due to social selection or recall bias. Furthermore, most previous research into the effects of housing on health has been concerned with tenure (Lewis et al., 1998; Weich and Lewis, 1998), and the effects of structural problems, such as damp or infestation (Platt et al., 1990; Hopton and Hunt, 1996; Smith and Mallinson, 1997;
1353-8292/01/$ - see front matter r 2001 Elsevier Science Ltd. All rights reserved. PII: S 1 3 5 3 - 8 2 9 2 ( 0 1 ) 0 0 0 1 9 - 3
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Acheson, 1998; Weich and Lewis, 1998; Marsh et al., 2000). There have been very few studies of the associations of the effects of the wider environment outside the home. One exception was a survey of a random sample of residents in West Central Scotland, which identified three ‘psychosocial benefits’ associated with the home: the home as haven, as a locus of autonomy and as a source of status (Kearns et al., 2000). Statistically significant associations were found between all three dimensions and respondents’ perceptions of the ‘area environment’ (such as litter, vandalism and crime), and the ‘people in the area’ (including noise, other types of disturbance, and ‘neighbourhood reputation’). However, only the latter remained statistically significant after adjusting for housing tenure and problems associated with the dwellings themselves, such as damp. There is also evidence that those living in urban areas experience worse physical and mental health than those living in rural or suburban areas (Lewis and Booth, 1994; Meltzer et al., 1995; Dorling, 1997). The mechanisms underlying this association remain poorly understood, although there is now little support for the oncepopular notion of geographical drift (Lewis et al., 1992; Verheij, 1996). It is not yet known, however, to what extent higher rates of morbidity and mortality in urban areas are explained by individual-level socio-economic deprivation, such as low income or unemployment (Sloggett and Joshi, 1994; Dunn, 2000). One important aspect of life in urban areas is the built environment. Defined broadly, the built environment includes many characteristics of places that cannot be reduced to the characteristics of the people who live there, such as housing form, roads and footpaths, transport networks, shops, markets, parks and other public amenities, and the disposition of public space. The built environment is likely to affect important aspects of the environment in which people live in both direct ways, such as effects on traffic, noise and air pollution, and in less tangible ways, by influencing the sense of community and ‘social capital’ in an area (Dunn, 2000). Evaluating associations between the built environment and health is therefore highly challenging, particularly when attempting to elucidate the mechanisms that might link these. Two previous studies of the effects of urban regeneration on mental health assessed the impact of improvements in the built environment that were intended to increase security and community participation, even though both were primarily ‘bricks and mortar’ interventions. Although both treated urban regeneration as a ‘black box’ intervention, both found that improvements in the built environment were associated with lower levels of anxiety and depression (Halpern, 1995; Dalgard and Tambs, 1997). Both studies were, however, limited by measures of the built environment that relied on
residents’ perceptions, and may therefore have been prone to recall bias. The dearth of empirical research into the effects of specific features of the built environment on health may be partly due to the absence of reliable and valid ‘objective’ measures. One notable exception was the study of young married women living on a housing estate in south–east London (Birtchnell et al., 1988). In this study, Birtchnell and his colleagues rated several aspects of the built environment including housing form, density, accessibility, entrance type and position, and control over the ‘buffer zone’ between private and public space, using a 15-item scale of ‘design variables’. Although this scale was based on previously published research, the authors did not report its psychometric properties. Birtchnell and his colleagues (1988) found that, compared with non-depressed controls, depressed women were significantly more likely to be living in blocks with raised walkways than in brick or concrete houses, or in tower blocks. The present study was conducted prior to an evaluation of the effects of an urban regeneration programme on the mental health of local residents in an electoral ward in north London. The main initial thrust of the regeneration programme was external refurbishment, and improving the quality of the built environment. We hypothesised that improvements in the built environment would be associated with a reduction in the prevalence of depression. The aim of the present study were twofold; first, to evaluate the psychometric properties of a set of ‘objective’ measures of the built environment, and second, to validate this by evaluating associations with the prevalence of depression, among residents in two inner city electoral wards in north London.
Methods The present study was conducted as a preliminary to a prospective cohort study, comparing changes in mental health over three years among individuals living in two electoral wards in north London. One of these wards was the site of a programme of improvements to the built environment, as part of the Capital Challenge scheme, while the other was selected as a control, for the purposes of evaluation. The control ward was chosen on the basis of its similarity to the intervention ward in socio-demographic composition and the character of its housing, using a variety of sources. This ward was also chosen because there was no similar urban regeneration programme underway at the time. The estimated populations of the experimental and control wards in 1999 were 6260 and 9549, respectively. Respondents to the main survey were selected in two stages using random probability sampling methods. The
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postcode address file (PAF) was used as the sampling frame for selecting about 1300 addresses within each ward. All addresses that were residential and occupied were eligible, and up to 2 adults (aged 16+) were sampled at random within each household using a Kish grid technique. Once selected, no substitutions were allowed. The household response rate was 64%. Eightythree percent of selected individuals within participating households agreed to take part, resulting in a survey sample of 1902. Housing areas Each of the two study wards was sub-divided into discrete housing areas. This was done a priori by one of the authors (EB), a trained architect, prior to collecting any other data. A housing area was defined as a geographically bounded area in which the majority of the housing is homogeneous in form and character. There was considerable variation in the number of dwellings within each housing area, which ranged from a tower block to streets of terraced houses. Thirty-three housing areas were enumerated in the experimental ward, and 53 in the control ward. Built environment site survey The built environment site survey checklist (BESSC) comprised a standardised list of items to be rated. Items included the predominant form, height and age of housing, number of dwellings and type of access, provision of gardens, use of public space, amount of derelict land, security, and accessibility of local shops and amenities (see Appendix A). Twenty-five out of 27 items in the BESSC had fixed categorical responses. The two remaining items required the researcher to rank features of the built environment (e.g. the proportion of space used in particular ways), and to estimate the distance from the centre of the ‘housing area’ to a range of amenities (e.g. bus stop). Checklist items were drawn from several sources, including three national housing surveys, namely the Housing Attitudes Survey (Department of the Environment, 1994), Housing in England (Office for National Statistics, 1997), and British Social Attitudes (SCPR, 1997). Other sources of items included texts on urban design (Bentley et al., 1985; Coleman, 1985), and published studies in this field (Birtchnell et al., 1988; Perkins et al., 1992). The BESSC was piloted and amended before final use. Data collection Each housing area was allocated an identifying number. Every third area in the experimental ward was selected for the reliability study. These 11 areas were
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rated independently by two researchers, using BESSC. Both researchers were postgraduate students in urban design with backgrounds in architecture. One of the researchers also used the BESSC to rate the other 75 housing areas across the two wards. The researchers were briefed prior to data collection by one of the authors (EB), to ensure consistency in their understanding of each of the items on the checklist, and to clarify any misunderstandings. Briefing took approximately 3 h. Within each housing area, the researchers were instructed to locate and mark the following onto maps: bus stops, GP surgeries, food stores, newsagents, pubs and schools. Data were collected in April and May, 1999. Prevalence of depression The prevalence of depression was assessed using the Center for Epidemiologic Studies Depression scale (CES-D) (Radloff, 1977; Roberts and Vernon, 1983; Beekman et al., 1997). This brief, 20-item self-report measure was developed as a measure for identifying probable cases of clinically significant depression in epidemiological surveys. Each item includes four response categories, and is scored using a Likert scale (0–3). Those scoring 16 or more (out of a possible score of 60) were classified as cases, in keeping with previous studies (Frerichs et al., 1981; Harlow et al., 1999). Although results are presented here for ‘cases’ of depression, there was no reason to expect that using CES-D score as a continuous variable would lead to different results (Anderson et al., 1993). Respondent attitudes Survey respondents were asked to rate their satisfaction with ‘‘the area as a place to live’’. Responses were coded on a five-point scale, ranging from ‘very satisfied’ to ‘very dissatisfied’. These were then dichotomised, with one indicating ‘fairly dissatisfied’ or ‘very dissatisfied’, and 0 otherwise. Respondents were not given any advice about the geographical boundaries of their area when answering this question. Statistical analysis All analyses were undertaken using Stata (Stata Corporation, 1999). For the BESSC reliability study, inter-rater reliability was assessed using the kappa and weighted kappa statistics for categorical variables and item rankings, and intra-class correlation coefficients for continuous measures. The kappa statistic is the most widely used measure of inter-rater reliability, and reflects the difference between the rate of agreement between two raters and that expected by chance. Where there are more than two ordered categories, the weighted kappa statistic reflects the degree of difference between raters
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(in terms of the number of categories between their respective observations), rather than simply whether or not they agree (Armitage and Berry, 1994). BESSC items with good inter-rater reliability or better (kappa X0.5) were included in subsequent analyses. These items are shown in the Appendix B. Associations between responses to BESSC items and (i) the prevalence of depression, and (ii) dissatisfaction with the area as a place to live, were assessed using odds ratios (with 95% confidence intervals), estimated by means of logistic regression. These analyses were undertaken using the survey commands within Stata (Stata Corporation, 1999), which adjusts standard errors for the stratification of the sample by electoral ward, and the clustering within housing areas and households (Huber, 1981). Data were weighted by household size, in order to adjust point estimates for the probability of selection.
Results Inter-rater reliability of BESSC items Table 1 shows the degree of inter-rater reliability for the full list of categorical items in BESSC, across the 11
housing areas surveyed for the reliability study. Low kappa coefficients were found when comparing the rankings used to rate the division of space within each housing area (BESSC item 7, Appendix A), the highest of which was 0.46 (SE 0.23) (p ¼ 0:02), for shared garden/open space. Table 2 shows the intra-class correlation coefficients for the estimated distances from the centre of the housing area to the nearest amenity of each type (BESSC item 19). Overall, fifteen out of 25 categorical BESSC items had kappa coefficients of X0.50.
Associations with the prevalence of depression and resident satisfaction The prevalence of depression was 39.0%, as defined by a cut-off of 15/16 on the CES-D. This rate did not vary to a statistically significant degree between the two study wards (w2 ¼ 0:51; df ¼ 1; p ¼ 0:47). Statistically significant associations were found between the prevalence of depression and five of the fifteen BESSC items with satisfactory inter-rater reliability. After adjusting for the clustering of respondents within housing areas (and wards), statistically significant associations were
Table 1 Inter-rater reliability of the site survey items, showing the number of response categories, agreement between raters, and kappa statistic (with standard error), for each item. Items with kappa values X0.50 are shown in bold Item (number: see Appendix A)
Number of categories
% agreement
Kappa (SE)
Housing form Number of storeys of buildings Type of access to dwellings No. of dwellings per entrance No. of dwellings in housing area Age of housing Number of trees in public domain Nature of space outside dwellings Private gardens: proportion Private balconies: proportion Shared recreational space Number of vehicular entrances Number of pedestrian entrances Entrances visible from roads Entrances visible from footpaths Parking arrangements Number of children’s play areas Footpaths overlooked Open spaces overlooked Disused buildings Derelict land Evidence of vandalism Evidence of graffiti Territorial functioning Neighbourhood watch signs
2 5 3 8 6 5 5 3 3 3 2 5 5 5 5 5 5 3 3 2 2 3 3 3 2
81.8 86.4 81.8 87.3 86.4 84.9 84.9 77.8 81.8 77.3 100 86.4 84.1 77.3 68.2 36.4 84.9 81.8 45.5 90.9 80.0 36.4 90.9 45.5 90.9
0.54 (0.30) 0.57 (0.20)a 0.72 (0.21) 0.64 (0.21)a 0.67 (0.22)a 0.64 (0.20)a 0.65 (0.22)a 0.61 (0.22) 0.65 (0.26) 0.52 (0.25) 1.00 (0.24) 0.48 (0.20)a 0.65 (0.22)a 0.50 (0.20)a 0.04 (0.18)a 0.21 (0.13) 0.44 (0.20)a 0.05 (0.14) 0.26 (0.17) 0.62 (0.28) Fb 0.07 (0.11) 0.76 (0.24) 0.23 (0.13) 0.0 (0.0)
a b
weighted kappa. kappa statistic could not be calculated because of empty cells.
p 0.04 0.002 0.0003 0.001 0.001 0.0008 0.002 0.003 0.006 0.02 o0.0001 0.008 0.002 0.006 0.42 0.05 0.01 0.63 0.06 0.01 Fb 0.26 0.001 0.04 0.50
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found between the prevalence of depression and living in housing areas where (i) most properties had deck access; (ii) properties were mainly built after 1940; (iii) fewer than one-quarter of homes had a private garden; (iv) there was a shared recreational space; and (v) many patches of graffiti were observed (Table 3). No statistically significant associations were found between the prevalence of depression and the distance from the centre of the housing area to the nearest bus stop, public house or school. A statistically significant difference was found between the two study wards in the proportion of respondents who were dissatisfied with their area ‘as a place to live’ (w2 ¼ 6:94; df ¼ 1; p ¼ 0:008). More of those living in the experimental ward (14.4%) than in the control ward (10.3%) were dissatisfied in this way. After adjusting for the clustering of respondents within housing areas (and wards), the pattern of associations with BESSC items almost identical to that found
Table 2 Intra-class correlation (icc) coefficients (with standard errors) for ratings of distance from centre of housing area to nearest amenities, for two raters Amenity
icc coefficient (SE)
p
Nearest Nearest Nearest Nearest Nearest
0.64 0.07 0.28 0.94 0.93
0.01 0.41 0.18 o0.0001 o0.0001
bus stop GP surgery newsagent public house school
(0.18) (0.31) (0.29) (0.03) (0.03)
between the latter and the prevalence of depression. Statistically significant associations were found between dissatisfaction with their area ‘as a place to live’ and all but one of the BESSC items that were associated with the prevalence of depression to a statistically significant degree. The one difference in associations with these two outcomes was the proportion of homes with private gardens, for which the association with ‘dissatisfaction’ did not reach statistical significance (Table 4). No statistically significant associations were found between dissatisfaction with the area as a place to live and the distance from the centre of the housing area to the nearest bus stop, public house or school.
Discussion It is still not known whether, or how, the built environment affects health, independent of individuals’ material circumstances. The present study represents a preliminary attempt to develop a set of reliable measures of the characteristics of the built environment in urban settings, with which to further address these questions. There was relatively little published empirical evidence to guide the choice of items, and consequently we opted for items with the greatest face validity, and those that were likely to be of acceptable reliability. The majority of items in our checklist were of satisfactory inter-rater reliability. Of the 25 items in Table 1, kappa coefficients for only 10 were below 0.5, a value that reflects moderate to good inter-rater reliability (Stata Corporation, 1999). Eleven items had kappa
Table 3 Odds ratios (95% CI) for bivariate associations between the prevalence of depression and BESSC items with satisfactory inter-rater reliability (X0.50) BESSC item
OR (95% CI)
p
Non-traditional housing form (v traditional) Most buildings >3 storeys (vp3 storeys) Deck access (v other types of access) >5 dwellings per entrance (vp5) o50 dwellings in housing area (vX50) Properties built 1940–1969 (v pre-1940) Properties built 1970 or later (v pre-1940) o5 trees in public domain (vX5) Non-private space outside properties (v private) o 14 homes with private gardens ðvX14Þ o 14 homes with private balconies ðvX14Þ No shared recreational space (v any) 3–9 pedestrian entrances to housing area ðvp2Þ X10 pedestrian entrances to housing area ðvp2Þ Building entrances visible from roads (v none) Disused buildings (v none) Some patches of graffiti (v none) Many patches of graffiti (v none)
1.24 1.29 1.57 0.87 0.89 1.88 2.36 1.18 1.15 1.75 0.81 0.52 0.81 1.02 0.73 1.15 1.28 2.12
0.41 0.22 0.03 0.46 0.51 0.009 o0.001 0.43 0.65 0.03 0.35 0.008 0.37 0.90 0.14 0.36 0.32 0.006
(0.73–2.10) (0.85–1.95) (1.05–2.34) (0.52–1.35) (0.61–1.28) (1.18–3.00) (1.53–3.65) (0.77–1.81) (0.63–2.12) (1.07–2.85) (0.52–1.27) (0.32–0.84) (0.51–1.29) (0.74–1.41) (0.49–1.11) (0.84–1.58) (0.79–2.09) (1.25–3.59)
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Table 4 Odds ratios (95% CI) for bivariate associations between dissatisfaction with ‘the area as a place to live’ and BESSC items with satisfactory inter-rater reliability (X0.50) BESSC item
OR (95% CI)
p
Non-traditional housing form (v traditional) Most buildings >3 storeys (vp3 storeys) Deck access (v other types of access) >5 dwellings per entrance (vp5) o50 dwellings in housing area (vX50) Properties built 1940–1969 (v pre-1940) Properties built 1970 or later (v pre-1940) o5 trees in public domain (vX5) Non-private space outside properties (v private) o 14 homes with private gardens ðvX14Þ o 14 homes with private balconies ðvX14Þ No shared recreational space (v any) 3–9 pedestrian entrances to housing area ðvp2Þ X10 pedestrian entrances to housing area ðvp2Þ Building entrances visible from roads (v none) Disused buildings (v none) Some patches of graffiti (v none) Many patches of graffiti (v none)
1.52 0.83 2.90 0.70 1.29 8.56 6.51 0.89 1.29 2.26 0.58 0.23 0.85 1.22 0.68 0.87 1.28 2.12
0.28 0.60 0.004 0.39 0.48 o0.001 o0.001 0.77 0.53 0.16 0.19 0.002 0.71 0.58 0.38 0.68 0.32 0.006
coefficients X0.6 (indicative of ‘substantial’ reliability), of which one (presence of any shared recreational space within the housing area) had a kappa value of 1.0. Kappa coefficients were lower where researchers were required to rank the proportion of space within housing areas occupied by different environmental features. Intra-class coefficients for the distance between the centre of the housing area and different amenities (using maps) varied from the very high (>0.9) for the nearest public house and school, respectively, to the very low (o0.1) for the nearest GP surgery. There was evidence of statistically significant associations between five measures of the built environment (all of which had kappa values of X0.50) and the prevalence of depression. In particular, those who were identified as cases of depression were more likely to be living in housing areas characterised by newer (post-1940) properties, with deck access but few private gardens, and with shared (public) recreational space(s) and evidence of many patches of graffiti. Together, these items would appear to describe the type of inner city, local authority-owned housing estate with which drug misuse and crime are often associated. Of these, only the proportion of homes without gardens was not associated with residents’ dissatisfaction with their own area ‘as a place to live’ to a statistically significant degree. There was no evidence of any statistically significant associations between depression or dissatisfaction and distance to any of the three amenities whose location was identified consistently in the reliability study, namely the nearest, bus stop, school or public house. The
(0.71–3.27) (0.41–1.70) (1.42–5.91) (0.30–1.59) (0.63–2.63) (3.63–20.18) (2.89–14.66) (0.41–1.95) (0.58–2.86) (0.73–7.05) (0.26–1.31) (0.09–0.57) (0.35–2.04) (0.59–2.53) (0.29–1.62) (0.46–1.67) (0.79–2.09) (1.25–3.59)
pattern of associations with the prevalence of depression, in particular, was consistent with the results of Birtchnell et al. (1988), although the latter study was restricted to women. Taken as a whole, our findings provide support for the reliability of (at least) fifteen items, and for the concurrent validity of five items from the BESSC. However, the sample size for the reliability study was relatively small, comprising just 11 housing areas, and standard errors were large. Failure to find statistically significant inter-rater reliability for some of items may therefore have been due to type II error. Nevertheless, rates of agreement were high, exceeding 70% for 21 out of the 25 categorical items shown in Table 1. Estimates of inter-rater reliability reached statistical significance at the level of po0:01 for 15 out of the 35 items analysed. It is possible that failure to find more statistically significant associations with the prevalence of depression, or with dissatisfaction with the area ‘as a place to live’ were also due to the methodological limitations of the study. Both study wards, though not contiguous, were located within the same London Borough, and the homogeneity of housing areas on many of the BESSC items may therefore have precluded the emergence of strong associations with these two outcomes. Indeed, the control ward was chosen specifically because it resembled the experimental ward in the character of its housing stock. One strength of this study was the a priori definition of housing area boundaries. Although there is evidence that architects’ judgements, particularly in terms of
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aesthetics, differ from those of the general population (Devlin and Nasar, 1989; Halpern, 1995), the purpose of this study was to develop and evaluate an ‘objective’ measure of the built environment. Although there has been a great deal of research into the effects of housing on health, this has been based almost exclusively on the characteristics of individual homes, housing tenure, or residents’ satisfaction (Kearns et al., 2000). While our approach may be criticised for not incorporating residents’ views about the boundaries of housing areas, it was notable that we found associations between ratings of researcher-defined housing areas and residents’ satisfaction without providing the latter with any advice about the geographical boundaries of ‘their area’. One important limitation is that these findings, and the BESSC itself, may not be generalisable to other urban areas, and are unlikely to be applicable in suburban or rural settings. In the first instance, further research is needed to validate this measure in other urban settings. Conclusions Our findings suggest that it is both possible and feasible to rate the characteristics of the built environment in an urban setting independent of residents’ subjective perceptions. Most items, excluding those that required researchers to rank the use of land, showed at least moderate inter-rater reliability. Although further work is now required to refine and validate the measures described in this paper, in other independent areas, they may well prove useful in the further study of the effects of the built environment on physical and mental health. Further research is also needed to determine the possible mechanisms underlying associations between living in areas characterised by (for example) post-war housing and higher rates of depression.
Acknowledgements We would like to thank Ken Brodie and Juliet Matthews for collecting the site survey data, and Haroula Baladimou for collating it. We are also grateful to David Walker, of the London Borough of Camden, for providing us with demographic data about the two study wards.
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Non-traditional (Tower block/Slab block/Perimeter block/Cluster/Ribbon/Other) 2. How many storeys high are the majority of the buildings? 1 2 3,4 5–9 10+ 3. What type of access do most dwellings have? Direct from Deck access Internal corridor street or garden or stairwell 4. What is the typical number of dwellings per main entrance? (Main entrance defined as first door or gate into building) 1 2 3 4 5 6–9 10–19 20+ 5. Roughly how many dwellings are there in the housing area? 1–5 5–9 10–19 20–49 50–99 100+ 6. Approximately when was the housing built? Pre-1914 1914–1939 1940–1969 1970–1989 1990+ Space around the buildings 7. How is the open space divided up? (Rank the following, assigning 1 for the greatest proportion of space) Derelict/unused land Roads/footpaths Private gardens Shared garden/recreation space Parking areas 8. How many trees are visible in the public domain? None o5 approximately 5–9 approximately 10–19 20+ 9. What is the nature of the space immediately outside most front doors (i.e. doors to individual dwellings)? Private (Garden/Terrace/Corridor or stairwell) Shared (Garden/Terrace/Corridor or stairwell) Public (Public area/ Footpath/ External or semi-external corridor) 10. Approximately what proportion of dwellings have their own private garden space? Less than 14 Between 14 and 12 More than 12
Appendix A. Built Environment Site Survey Checklist (BESSC)
11. Approximately what proportion of dwellings have their own private balcony or terrace? Less than 14 Between 14 and 12 More than 12
Predominant characteristics of buildings 1. What is the predominant housing form? Traditional (Detached/Semi-detached/Terraced)
12. Does the housing area include any shared garden or other recreational open space? No Yes
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13. Roughly how many vehicular entrances are there into this housing area? 1 2 3,4 5–9 10+ 14. Roughly how many pedestrian entrances are there into this housing area? 1 2 3,4 5–9 10+ 15. On the whole, how many main entrances to buildings are visible from the main vehicular routes through the area? (main entrance defined as first door or gate into buildings) All Most Some Hardly any None 16. On the whole, how many main entrances to buildings are visible from the main pedestrian routes through the area? (main entrance defined as first door or gate into buildings) All Most Some Hardly any None 17. What are the parking arrangements (mainly)? None Offstreet only Predominantly private parking Predominantly public courts Mixed Facilities and accessibility 18. How many children’s play areas does the housing area have? None 1 2 3 4+ 19. From about the mid-point of the development, roughly how far is it to the following? (can calculate from map) Nearest bus stop Nearest GP surgery Nearest newsagent Nearest pub Nearest school
24. Are there signs of vandalism (e.g. broken telephone boxes, broken windows, damaged equipment) within the housing area? No Some signs Many signs 25. Are there patches of graffiti in the housing area? No Some signs Many signs 26. Are there signs of territorial functioning in the area? (e.g. decorated gardens/balconies, nameplates, window boxes) No Some signs Many signs 27. Are there any neighbourhood watch signs? No Yes
Appendix B. Items with satisfactory inter-rater reliability (kappa X0.50), and codings used to test for associations with the prevalence of common mental disorders. Numbers in brackets refer to full site survey checklist, BESSC, shown in Appendix A 1. Housing form (BESSC 1) What is the predominant housing form? 1=Traditional, 2=Non-traditional 2. Number of storeys (BESSC 2) How many storeys high are the majority of the buildings? 1=3 or fewer, 2=More than 3 3. Type of access (BESSC 3) What type of access do most dwellings have? 1=Access from street, garden, internal corridor or stairwell, 2=Deck access
Safety and security 20. Roughly what proportion of the footpaths/pavements through the development/area are overlooked by dwelling windows (i.e. windows no more than 10–15 m away)? Less than 14 Between 14 and 12 More than 12
4. Number of dwellings per entrance (BESSC 4) What is the typical number of dwellings per main entrance? 1=5 or fewer, 2=More than 5
21. On the whole, are the open spaces/play areas overlooked by dwelling windows? None Some Mostly
5. Number of dwellings in housing area (BESSC 5) Roughly how many dwellings are there in the housing area? 1=49 or fewer, 2=50 or more
22. Are any disused buildings (not vacant dwellings) evident in the housing area? No Yes
6. Age of housing (BESSC 6) Approximately when was the housing built? 1=pre-1940, 2=1940–1969, 3=1970 or later
23. How much of the land within the housing area seems to be derelict or unused? Less than 14 Between 14 and 12 More than 12
7. Trees (BESSC 8) How many trees are visible in the public domain? 1=5 or more, 2=Fewer than 5
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8. Space outside dwellings (BESSC 9) What is the nature of the space immediately outside most front doors? 1=Private, 2=Non-private 9. Private garden (BESSC 10) Approximately what proportion of dwellings have their own private garden space? 1= 14 or more, 2=Less than 14 10. Private balcony or terrace (BESSC 11) Approximately what proportion of dwellings have their own private balcony or terrace? 1=14 or more, 2=Less than 14 11. Shared recreational space (BESSC 12) Does the housing area include any shared garden or other recreational open space? 1=Yes, 2=No 12. Number of pedestrian entrances (BESSC 14) Roughly how many pedestrian entrances are there into this housing area? 1=Fewer than 3, 2=3–9, 4=10 or more 13. Entrances visible from road? (BESSC 15) How many entrances to buildings are visible from the main vehicular routes through the area? 1=Any, 2=None 14. Disused buildings (BESSC 22) Are any disused buildings (not vacant dwellings) evident in the housing area? 1=No, 2=Yes 15. Graffiti (BESSC 25) Are there patches of graffiti in the housing area? 1=No, 2=Some, 3=Many
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