HISCOCK

Journal of Social Issues, Vol. 59, No. 3, 2003, pp. 527--546

Residents and Residence: Factors Predicting the Health Disadvantage of Social Renters Compared to Owner-Occupiers Rosemary Hiscock∗ Karolinska Institutet

Sally Macintyre MRC Social & Public Health Sciences Unit

Ade Kearns University of Glasgow

Anne Ellaway MRC Social & Public Health Sciences Unit

Numerous studies have found that owner-occupiers live longer and stay healthier than renters. Epidemiologists often view housing tenure as a proxy for economic circumstances rather than as having directly health-promoting or damaging effects. Housing researchers, on the other hand, have tended to study physical and psychosocial aspects of housing that might directly impact upon health. Linking these two literatures, we analyzed nearly 3,000 postal questionnaires from a stratified random sample of Scottish adults. In particular, we examined differences between owners and social renters that might explain observed tenure differences ∗ Correspondence concerning this article should be addressed to Rosemary Hiscock at Family Medicine Stockholm, Karolinska Institutet, Alfred Nobels All´e 12, 141 83 Huddinge, Sweden [e-mail: rosemary.hiscock@klinvet.ki.se].

The Transport, Housing and Wellbeing Study on which this article is based was supported by the ESRC Health Variation Programme (grant no. L128251017 1997–2000). The analysis described herein was undertaken for the first author’s doctorate. The authors would like to thank the respondents for filling out the questionnaire; Margaret Reilly, Lindsay Macauley, and Barbara Jamieson for help with the data collection process; and Carol Nicol and Geoff Der for help with computing and statistics. Sally Macintyre and Anne Ellaway are employed by the UK Medical Research Council as was Rosemary Hiscock at the time this research was undertaken.

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in health. Personal characteristics explained much of the difference between owners and social renters, but some dwelling and neighborhood characteristics also played a role.

Inequalities in health have been a long-standing focus of British research (Townsend & Davidson, 1988) and more recently also a focus of policy (Department of Health for England and Wales, 1999). Inequalities in health have been noted between different forms of housing tenure. The term “housing tenure” refers to occupancy, by either the owner(s) or renter(s), of a housing unit (e.g., U.S. Department of Commerce, 2001). People who own their homes, owner-occupiers, are those who either own their homes outright or are buying them through a mortgage.

Rented accommodation can be divided into social and private rented. Social rented accommodation is managed or at least subsidized by public sources (Best, 1996).

Social rented properties are often owned by the Government (in which case they are also known as public rented) or housing associations (voluntary organizations that provide not-for-profit housing for low-income people).

Owner-occupiers tend to be healthier than those who rent their homes. These health differences could be the result of personal differences between the inhabitants of rented and owner-occupied homes, or of differences between the characteristics of the housing, or both. Kemeny (1992) argues that in the past, housing has not been conceptualized as “residence” where people with particular personal characteristics reside inside housing with particular characteristics. In this article, we apply these two perspectives of personal and housing characteristics to a consideration of possible explanations for observed tenure differences in health.

After reviewing literature in epidemiology and housing studies, we analyze data from a survey of nearly 3,000 Scottish adults to assess the relative contributions of personal and housing characteristics to various facets of health.

Knowing whether housing is itself a determinant of health is important for policy, as it can help determine, for example, whether resources are better put into improving social rented housing or into employment schemes. Additionally, research such as ours can help to focus resources on those aspects of housing that are most responsible for good health.

Are Health Inequalities Simply the Result of Differences in the Personal Characteristics of Owners and Renters?

Epidemiological research has consistently reported that in a number of countries, owner-occupiers live longer and are healthier than renters, particularly social renters. For example, Filakti and Fox (1995) linked tenure in the English and Welsh Census to subsequent death registration. Owner-occupiers had the lowest mortality and Local Authority renters (a group of social renters) had the highest mortality by follow-up in the 1970s and the 1980s. The greater longevity of British owner-occupiers was also noted by Fox and Goldblatt (1982) and by Kogevinas

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(1990) and Leon and Wilkinson (1989), focusing on cancers. Macfarlane and Mugford (1984) observed lower infant mortality in owner-occupied households in Britain. In Sweden, Sundquist and Johansson (1997) also found lower mortality among owners. Ecological studies suggest that areas in Britain with higher rates of owner-occupation have lower mortality (Phillimore, Beattie, & Townsend, 1994; Sloggett & Joshi, 1994, 1998).

Self-reported and clinically diagnosed morbidity, or poor health, has also been linked to housing tenure in censuses and through nationwide longitudinal and cross-sectional studies in all age groups. In Britain, owner-occupiers have been found to report less chronic illness (Arber, 1989; Breeze, Sloggett, & Fletcher, 1999; Gould & Jones, 1996; Sloggett & Joshi, 1998); to make fewer general practitioner (GP) visits (Benzeval & Judge, 1996; Carr-Hill, Rice, & Roland, 1996); and to have higher scores on clinical and self-reported physical, global, and mental health measures (Arber & Cooper, 1999; Blaxter, 1990; Fogelman, Fox, & Power, 1989; Macintyre, Hiscock, Kearns, & Ellaway, 2001). Owner-occupiers have been reported to have a lower incidence of cancer than social renters in England and Wales (Kogevinas, 1990) and Italy (Faggiano, Zanetti, & Costa, 1994).

A potential explanation for the health disadvantage of social renters compared to owner-occupiers is that people living in social rented housing have less healthy demographic characteristics such as age, sex, and marital status. Social renters are on average older, more likely to be female, and more likely to be single than owner-occupiers (Macintyre, Hiscock, Ellaway, & Kearns, 2000); older people, women, and single people are less likely to be healthy (Macintyre, 1986). The observed relationship between tenure and health is not simply the result of personal demographic characteristics however; most studies take such characteristics into account when reaching their conclusions.

Often tenure differences in mortality and morbidity are viewed as being the result of differences in economic resources variously described, for example, as “material well-being” (Phillimore, Beattie, & Townsend, 1994), “income” (Sloggett & Joshi, 1994), and “material deprivation” (Baker, 1997). However, many of the studies reported above control for deprivation in some way. Sundquist and Johansson (1997) controlled for years of education; Sloggett and Joshi (1998) controlled for area deprivation, individual unemployment, social class, and car access; and Arber and Cooper (1999) controlled for social class and household income. All found that tenure still predicted health. Thus these studies suggest that tenure differences in health are not the result simply of different demographic and socioeconomic characteristics among owners as compared with renters.

Other studies have found that after controlling for socioeconomic circumstances, such as social class, the relationship between tenure and health disappears for some measures for some population groups. Mortality in single British women (Moser, Pugh, & Goldblatt, 1988), suicide in Swedish people under 30 and over 49 (Johansson, Sundquist, Johansson, Qvist, & Bergman, 1997), mortality and disability in American older men (Goldman, Korenman, & Weinstein, 1995), disability

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in British older men (Arber & Ginn, 1993), chronic illness in married people from the West of Scotland (Macintyre, Hiscock, Kearns, & Ellaway, 2001), and serious illness in Norwegian older people and mental health in Norwegian older men (Dahl & Birkelund, 1997) were not differentiated by tenure after sociodemographic controls. Overall, however, most studies suggest that the relationship between housing tenure and some health measures persists even after sociodemographic controls.

Another strand of literature implies that differences in psychological characteristics between renters and owners could also be responsible for the health difference. Self-esteem, or the extent to which one views oneself positively or negatively (Rosenberg, 1965), has been found to be positively associated with health and socioeconomic status (Rosenberg, Schooler, Schoenbach, & Rosenberg, 1995). Mastery, or the extent to which one perceives one’s life chances to be under one’s own control (Pearlin & Schooler, 1978), has also been positively associated with health (Dew et al., 1994; Penninx et al., 1996), with socioeconomic status (Pearlin & Schooler, 1978), and with housing satisfaction (Seilheimer & Doyal, 1996). The direction of causation however is unclear. It is not known to what extent those with higher self-esteem and greater feelings of mastery are healthier or to what extent health creates higher self-esteem and mastery. Similarly it is unclear to what extent it is the case that those with higher self-esteem and greater feelings of mastery are more likely to become home owners, compared with the case where home ownership creates self-esteem and mastery.

However, in a sample of nearly 2,000 people in the West of Scotland, Macintyre, Ellaway, Der, Ford, and Hunt (1998) found that the magnitude of the relationship between tenure and either clinically measured or self-reported health did not attenuate greatly after controlling for either economic or psychological characteristics. This suggests that the relationship between tenure and health may not be solely due to the personal characteristics of inhabitants, and that features of housing may play a role.

Are Health Inequalities Between Owners and Renters Due to Differences in Their Housing?

One strand of the housing studies literature that may be relevant to tenure differences in health relates to the physical conditions of the home and area. A second strand relates to the meaning of home. Below we summarize some housing studies that exemplify work in each of these two strands.

Physical Conditions Numerous studies have documented associations between poor housing conditions and poor health (for reviews, see Evans, Wells, & Moch, this issue; Ineichen, 1993; Lowry, 1991; Thomson, Petticrew, & Morrison, 2000). A wide range

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of variables have received attention. One of general interest is the style of the dwelling—for example, whether it is a house or flat (e.g., Blackman, Evason, Melaugh, & Woods, 1989; McCarthy, Byrne, Harrison, & Keithley, 1985). Other variables represent amenity values of the housing, such as the presence of a garden (Townsend & Davidson, 1988). Some physical variables may have relevance for health in part because of what they represent to members of a household and people in the community. For example, housing can play an important role in a lifestyle that allows one to make positive comparisons of oneself to other people (MacLeod, Graham, & Johnston, 2001). So, just as it is likely to have high physical standards, a luxurious dwelling can provide a basis for making positive social comparisons.

The work just mentioned implies that tenure differences in health may reflect the extent that conditions of the home and area differ with owner-occupied versus rental housing. Other housing studies provide complementary support. Even though they may not have focused on health outcomes, they speak to differences in how owners and renters perceive the quality of their housing. For example, results of the third Scottish Survey of Consumer Preference in Housing (Pieda, 1996) suggest that conditions in the owner-occupied sector are more satisfactory than conditions in either the public rented or the private rented sector. The only aspect with which over 10% of owners were dissatisfied was storage, whereas public and private renters were dissatisfied also with heating, security, and the neighborhood.

A small body of intervention and longitudinal studies also have provided evidence of associations between physical housing conditions and health. For example, Hunt and McKenna (1992) looked at improved and nonimproved housing in social rented areas of Liverpool. Improved properties were significantly less likely to be damp and were least noisy. Inhabitants of improved housing reported fewer health problems including cardiovascular diseases, mental illness, and respiratory disease. The health data were self-reported and retrospective. However, the authors note that although adult health was reportedly poor, children’s health in the sample was reported to be good, suggesting that results were not due to reporting bias.

Many studies concerned with physical housing conditions and health have not controlled adequately for the personal characteristics of study participants.

Although the authors attribute the results of their studies to housing, it is possible that they really are a consequence of unmeasured personal characteristics (e.g., Blackman et al., 1989). Some personal characteristics, however, have been studied in detail by housing researchers. Somerville (1998), for example, discusses the implications for social exclusion of the concentrations of particular types of households (such as female-only and single parents) in social rented housing.

Those studies that have controlled for personal characteristics in studying relations between housing and health provide mixed evidence. In a sample of Glaswegians, Ellaway and Macintyre (1998) found that housing stressors (such as

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dampness), opinion of the local area, and housing type still predicted chronic illness and mental illness after controlling for the personal characteristics of income, age, and sex. However, they did not control for the psychological characteristics of their respondents.

Directly pertinent to tenure differences in health, Pell et al. (1999) used ecological and individual health measures in their analysis of the Scottish Housing Condition Survey (SHCS) 1996. They linked the SHCS (N = 20,000) to records of area National Health Service hospital admissions. Controlling for mean age of household, household size, dwelling type, rurality, area census characteristics, and housing conditions, as well as employment status and income after housing costs, they still found lower morbidity and mortality rates to be associated with owner-occupation.

In contrast, Mann, Wadsworth, and Colley (1992) did not find that tenure and health were associated after controlling for personal and housing circumstances (overcrowding and lack of amenities) in the longitudinal Medical Research Council National Survey of Health and Development. However, only one specific illness measure was used (lower respiratory health).

In summary, owner-occupiers tend to live in more satisfactory properties than social renters in terms of the condition of the home and the neighborhood in which the home is situated. Improvements in socially rented properties are associated with better health amongst their occupants. Thus it is likely that housing conditions are partly responsible for inequalities in health between social renters and owneroccupiers.

Meaning of Home If the relationship between tenure and health is not entirely determined by personal characteristics or physical housing characteristics, then the meaning of home (its psychosocial aspects) may be important. Much of the literature on the meaning of home has not been linked to health (Despres, 1991; Gurney, 1999; Madigan & Munro, 1991; Rainwater, 1966; Saunders, 1989). One study that does attempt to link the meaning of home and health is that of Dunn and Hayes (2000).

In a postal survey in Vancouver, Dunn and Hayes measured meanings of the home, sociodemographic and psychological characteristics of the residents, and physical conditions of the home and area. In multivariate analysis, tenure appeared to be less important for health than meanings of home such as privacy, pride in the home, and positive feelings about the area. However, tenure itself was not the focus of the study and it is not possible from the results provided to say which personal or housing characteristics attenuated the relationship between tenure and health. These findings should also be treated with caution because this was a cross-sectional study with a 9% response rate. All measures were self-reported

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and associations between housing and health variables could be due to a negative affectivity bias (i.e., some people are likely to answer any question more negatively than other people; Watson & Pennebaker, 1989). However, this study does provide suggestive evidence that the meaning of home may also affect health.

Summary The literature supports several hypotheses about possible explanations for observed associations between tenure and health. However, it appears that no study has empirically tested the relative importance of sociodemographic, psychological, housing condition, and meaning of home explanations for owner-occupiers’ health advantage over social renters. This will be the subject of the remainder of this article.

Method Study Design The Transport, Housing and Wellbeing Study involved a postal survey sent, in 1997, to 6,500 adults, sampled from the electoral roll, in the Glasgow and Clyde Valley Structure Plan Area in Scotland. A 50% response rate was achieved from three mailings, after excluding deaths and movers (N = 2,838; see Macintyre, Hiscock, Ellaway, & Kearns, 2000). The West of Scotland includes the poorest neighborhoods in Britain (such as Govan and Pollok in Glasgow, and Greenock and Inverclyde; Shaw, Dorling, Gordon, & Davey Smith, 1999). However, it also includes some very wealthy areas, such as Bearsden and Milngavie.

Measures The questionnaire included measures of health, personal, and housing characteristics (see Tables 1, 2, and 3). Health has many facets. Thus the survey included measures of chronic illness (limiting long-standing illness), global health (general health and GP consultations), and mental health (the Hospital Anxiety and Depression Scale, or HADS; Zigmond & Snaith, 1976). For the anxiety subscale the alpha was .83, and for the depression subscale the alpha was .80. Unfortunately, health can be measured only through self-report in a postal survey.

To measure personal characteristics, the questionnaire included indicators of demographic, economic, and psychological characteristics. Demographic measures included age, sex, and household type (a measure that encompassed marital status and the presence of other household members). Economic measures of net household income and occupation (later classified into Registrar General’s

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Social Classes) were available. The Rosenberg Scale (Rosenberg, 1965) measured self-esteem, and the Pearlin Scale (Pearlin & Schooler, 1978) measured mastery. For the self-esteem scale the alpha was .88, and for the mastery scale the alpha was .81. Low scores on these scales indicate low self-esteem and mastery.

To measure housing conditions, the questionnaire included 5 items on whether the physical conditions of the dwelling (damp, cold, noise, overcrowding, and state of repair) were a major (coded 3) or minor (coded 2) problem or not a problem at all (coded 1). There were 14 items, constructed similarly to the housing conditions items, on conditions in the neighborhood (respondents were asked whether the following items were a major problem, a minor problem, or not a problem: vandalism, litter and rubbish, smells and fumes, assaults or muggings, burglaries, disturbance by children or youngsters, speeding traffic, discarded needles or syringes, uneven or dangerous pavements, nuisance from dogs, reputation of the neighborhood, poor public transport, noise, and the people round here). The respective items were summed to provide housing and neighborhood conditions variables. For the housing conditions scale the alpha was .71, and for the neighborhood conditions scale the alpha was .87. A local amenities scale asked respondents how well placed their dwelling was for six amenities (general food stores, their doctor’s surgery, the nearest hospital with a casualty department, public transport, libraries, and pharmacies). Respondents rated their homes as “very well placed,” or “fairly well placed,” or “not very well placed,” or “not at all well placed.” The alpha for this scale was .82. A factor analysis of this scale produced one factor that explained 53% of the variance. Low scores on this factor indicate that the home was well placed for amenities. Neighborliness was measured by the number of neighbors with whom respondents exchanged small favors, such as watering plants while away.

Questions were asked also about the style of the dwelling. Respondents were asked to indicate whether their dwelling was detached, semidetached, a sandstone tenement flat, or another type of flat. Sandstone tenement flats were distinguished because this is a common housing type, mainly built during the 19th century to a high and durable standard for the middle classes in areas near city centers, and thus differing in construction, location, desirability, and types of inhabitants from “modern” flatted properties built usually to lower standards after the Second World War. Respondents also indicated whether their dwelling had a garden and, if so, whether it was shared with other households or was private. The luxuriousness of the dwelling was also measured by respondents’ estimation of its value; the number of rooms; whether it was worth more, the same, or less than others in the same street; and the number of consumer durables within the home from the following list: telephone, satellite or cable TV, double glazing, central heating, deep freezer or fridge freezer, washing machine, smoke alarm, burglar alarm, and security lighting.

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The meaning of home was also assessed: Measures of psychosocial benefits of home (protection, autonomy, and prestige) were developed from a factor analysis of a seven-item scale developed for the study (see Kearns, Hiscock, Ellaway, & Macintyre, 2000). For this scale the alpha was .88 and three factors explained 79% of the variance. Low scores on these factors indicate low protection, autonomy, and prestige.

The home may have more chance to exert an effect over time. Thus length of residence (in years) was also measured.

Thus the survey facilitates an analysis including sociodemographic and psychological personal characteristics, physical housing and neighborhood characteristics, and the meaning of home. We now describe our analysis of the data in two parts: firstly preliminary bivariate analysis and secondly more complex multivariate analysis using logistic regression and General Linear Modelling (GLM). SPSS version 9 was used for all analyses.

Results Bivariate Analysis In this section we consider whether tenure was significantly related to health, personal characteristics, and housing characteristics in bivariate analysis. We include the bivariate analysis here for several reasons. First, the results can be compared with bivariate results from other studies. Second, some researchers argue that multivariate analysis is a useful further step only if bivariate results are significant. Third, bivariate analysis may help explain puzzling results in multivariate analysis.

Unfortunately, we had too few private renters (n = 53) in our sample, so we compared only owner-occupiers and social renters. As expected, tenure was related to all measures of health in bivariate analysis (Table 1). Owners and social renters

Table 1. The Relationship Between Tenure and Health Variables Continuous variables GP consultations (last year)a Anxiety (HADS)b Depression (HADS)b Categorical variables General health (last year) fair or poor Limiting long-standing illness a

Social renters Mean N 5.5 952 8.0 859 6.1 892 % N 60.3 989 47.2 908

Owners Mean N 3.6 1646 6.6 1580 4.1 1588 % N 29.2 1683 24.8 1612

Effect size Eta2 .037 .027 .071 Phi .307 .229

The number of GP consultations ranged between 0 and 120.

The scales for anxiety and depression ranged between 0 and 21 with 21 being high. ∗∗∗ p < .001.

b

Sig ∗∗∗ ∗∗∗ ∗∗∗ ∗∗∗ ∗∗∗

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were compared through one-way analysis of variance for continuous variables and chi-square tests for categorical variables. We include measures of effect size (etasquare for continuous variables and phi/Cramer’s V for categorical variables) so that the relative strength of the variables’ relationship with tenure can be assessed.

Prevalence rates among the total sample are roughly comparable to other surveys. For example, the Scottish Health Survey (Scottish Office Department of Health, 1997) reports that 38% of working-age adults in their sample in Greater Glasgow reported limiting long-standing illness; 39% did so in our study.

A fifth of social renters described themselves as permanently sick compared with a twentieth of owners. For many permanently sick people, owner-occupation may not be an option as they may be unable to meet mortgage payments. Thus their health or economic status may cause their tenure position, rather than social renting causing ill health (Easterlow & Smith, 1997). To eliminate this potential confounding, all respondents who described themselves as permanently sick were removed from subsequent analysis, leaving 1,568 owners and 768 social renters.

All variables were significantly related to tenure in the bivariate analysis (p < .01) (Tables 2 and 3). In this article we discuss findings only where p < .01 rather than p < .05 because of the risk of Type I error due to the large number of statistical tests performed. Owners were significantly more likely than social renters to be younger, male, and cohabiting. They were significantly more likely than renters to have higher incomes, current or previous occupations of higher social classes, higher self-esteem, and higher mastery. Thus, as expected, owneroccupiers did have “healthier” personal characteristics than social renters.

Owners were also more likely than social renters to live in dwellings in good condition, houses rather than flats (except sandstone tenements), dwellings with a garden, dwellings with more consumer durables, high-value dwellings, and higher value dwellings than those nearby. Owners had lived in their dwellings for significantly fewer years than social renters. They were more likely to live in areas in better conditions, exchange favors with more neighbors, and have more amenities nearby. Owners reported receiving more protection, autonomy, and prestige from their homes than social renters. Thus, as expected, owner-occupiers, as well as displaying more health-enhancing personal characteristics than social renters, also inhabited superior dwellings, resided in better areas, and derived more positive meanings of home from these dwellings.

All the personal and housing characteristics discussed above, as well as being significantly related to tenure, were also significantly associated with at least one of the health measures on bivariate analysis (p < .01) in the expected direction.

For more details about the bivariate relationships, see Hiscock (2001); Macintyre, Ellaway, Hiscock, Kearns, and Der (2002); and Macintyre, Hiscock, Ellaway, and Kearns (2000). To test the relative importance of sociodemographic, psychological, housing condition, and meaning of home influences on the relationship between tenure and health, we employed multivariate analysis.

7.4 3.6 5.5 £28 124 16 yrs 24.6 .1 2.4 −.1 −.1 −.2

5 to 15b 6.1 1 to 15 5.0 e.g., central heating, burglar alarm, satellite/cable TV 0 to 9 6.7 £0 to £300 000 £62 382 number of years occupied the dwelling 0 to 88 yrs 14 yrs e.g., litter, reputation, traffic, assaults, burglaries 14 to 42b 20.6 how distant are, e.g., chemists, libraries, food stores −.4 to 3.8b −.1 number of neighbors who exchange small favors 0 to 50 2.8 .1 e.g., whether privacy is obtained from the home −3.9 to 1.1a a e.g., whether feels in control of the home −3.7 to 1.1 .1 e.g., whether other people would like a similar home −3.4 to 1.4a .2

damp, cold, noise, crowding, state of repair

.110 .145 .130 .283 .003 .122 .005 .016 .012 .011 .044

.020 .273 .032 .034

Owners Social renters Effect size mean mean (Eta2 ) 54 yrs £627 29.6 19.2

equivalized household income per month Rosenberg scale (Rosenberg, 1965) Pearlin scale (Pearlin & Schooler, 1978)

18 to 102 yrs £0 to £6557 12 to 40a 7 to 28a

Range 49 yrs £1378 31.5 20.5

Description

∗∗∗ ∗∗∗ ∗∗∗ ∗∗∗ ∗∗ ∗∗∗ ∗∗ ∗∗∗ ∗∗∗ ∗∗∗ ∗∗∗

∗∗∗ ∗∗∗ ∗∗∗ ∗∗∗

Sig

A high score on these scales indicates high self-esteem, mastery, protection, autonomy, or prestige, respectively. Scores on the self-esteem scale could range from 10 to 40; on mastery, from 7 to 28; and on the original meaning of home scale, from 7 to 35. The range of actual scores on the original meaning of home scale was also 7 to 35. b A high score on these scales indicates more problems. Scores on the problems with dwelling conditions scale could range from 5 to 15; on area conditions, from 14 to 42; and on the original area amenities scale, from 6 to 24. The range of actual scores on the original area amenities scale was also 6 to 24. ∗∗ p < .01. ∗∗∗ p < .001.

a

Variable Personal Age Income Self-esteem Mastery Housing Problems with dwelling conditions Number of rooms Number of consumer durables Value of dwelling Length of residence Problems with area conditions Problems with area amenities Neighborly favors Protection Autonomy Prestige

Table 2. Description of Continuous Variables in the Analysis and Bivariate Relationships With Tenure

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1. detached house 2. other house 3. sandstone tenement flat 4. other flat 1. none 2. shared 3. private 1. worth more 2. worth same 3. worth less

1. male 2. female 1. single lives alone 2. single lives with othersa 3. couple alone 4. couple lives with others 1. I & II professional & managerial 2. IIIn other nonmanual 3. IIIm skilled manual 4. IV & V semi- & unskilled manual

Description

19.7 50.7 10.0 19.7 5.8 17.4 76.9 21.9 73.7 4.4

43.2 56.8 18.7 11.9 30.9 38.5 40.3 28.2 17.1 14.5

Owners %

1.8 32.8 11.4 54.0 31.7 23.9 44.3 6.8 80.0 13.2

35.7 64.3 40.1 26.6 17.3 15.9 12.3 25.2 24.8 37.7

Social renters %

.231

.380

.387

.330

.347

.072

Effect size (Phi/Cramer’s V)

∗∗∗

∗∗∗

∗∗∗

∗∗∗

∗∗∗

∗∗

Sig

In the West of Scotland other household members tend to be children or parents but can also include lodgers, flatmates, grandparents, and siblings, for example. ∗∗ p < .01. ∗∗∗ p < .001.

a

Comparison homes Value compared to other houses nearby

Garden

Housing Dwelling type

Social class

Household type

Personal Sex

Variable

Table 3. Description of Categorical Variables in the Analysis and Bivariate Relationships With Tenure

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Multivariate Analysis In bivariate analysis a wide variety of variables reflecting personal and housing characteristics were related both to housing tenure and health. We used multivariate analysis to distinguish which variables were likely to be most helpful in understanding the association between housing tenure and health. Variables can appear to be significantly related in bivariate analysis, but this can be through another variable. When this variable is included in the analysis, the bivariate relationship may disappear or become attenuated. Thus multivariate analysis as well as bivariate analysis gives a more complete picture of the unique explanatory power of predictors.

Prior to the multivariate analysis, we tested for multicollinearity using multiple regression. The categorical variables were recoded into dummy variables so that they could be included in multiple regression. Multicollinearity is likely where the Variance Inflation Factor (VIF) is greater than five (Rogerson, 2001). The only variables this applied to were home protection and home autonomy. If protection or autonomy remained in a model after backward elimination, the analysis was repeated substituting autonomy for protection (or vice versa). Thus multicollinearity should be dealt with adequately in the analysis.

Finding the best predictors of health. Logistic regression was used to analyze the dichotomous health variables. Continuous health variables were analyzed using GLM. In both logistic regression and GLM, all variables were initially included in the model. Then nonsignificant variables were removed using backward elimination. We thus took an unashamedly empirical approach to the analysis. We did so because we were contrasting two strands of the literature rather than attempting to confirm previous results.

The final results of the backward elimination analysis are provided in Table 4.

We included variables in these models that were significant predictors of health only. We discuss variables that reached only the p < .01 level of significance for the reasons discussed above. We present Wald coefficients for the logistic regression analyses and eta-squares for the GLM analyses. These coefficients are standardized so they allow the relative importance of variables within each model to be compared; for example, age was the most important predictor and area conditions were the least important significant predictor of fair or poor general health.

The most important demographic predictor of health was age. Older people were more likely to be ill but were less likely to be anxious. Women tended to be more anxious and make more GP consultations. Perhaps surprisingly, after controls for housing and other personal characteristics, income was not a significant predictor of mental health although it was a strong predictor of chronic illness and global health. Social class was not a significant predictor of health in multivariate analysis. Nevertheless, for the most part, the results of this study confirm

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Table 4. Summary of Significant Variables ( p < .01) in Final Multivariate Models Predicting Health Fair or poor Limiting GP general health long standing illness consultations 1578 1721 1674

Health variable N Predictors Walda Age 51.3 Sex Household type Mastery 18.5 Self-esteem 17.5 Income 16.0 Dwelling conditions Neighborly favors Area conditions 15.5 Protectionb 2.7 Tenurec Tenured 8.0

Anxiety 1787

Depression 1787

Sig

Wald

Sig

Eta2

Sig

Eta2

Eta2

Sig

∗∗∗

131.8

∗∗∗

.028 .041

∗∗∗ ∗∗∗

∗∗∗

.015 .010

∗∗∗ ∗∗∗

.022 ∗∗∗ .024 .022 ∗∗∗ .009 .050 ∗∗∗ .031 .105 ∗∗∗ .130

∗∗∗ ∗∗∗ ∗∗∗

31.6 16.9

∗∗∗ ∗∗∗

∗∗∗ NS ∗∗

1.1 .1

NS NS

Sig

.005

∗∗

.005

∗∗

.006

∗∗

.001 .001

NS NS

.000 .000

NS NS

∗∗ ∗∗∗ ∗∗∗

.008

∗∗∗

.012 .003 .014

∗∗∗ NS ∗∗∗

a

Wald coefficients test the null hypothesis that the population coefficient is 0. Higher values denote a larger effect size than lower values. b Due to concerns of collinearity between protection and autonomy, the depression analysis was repeated substituting autonomy for protection. Autonomy was eliminated, suggesting that protection and autonomy are not equivalent predictors of depression. c Coefficients and significance for tenure before backward elimination process (with all variables, significant and nonsignificant, in the models). d Coefficients and significance for tenure after backward elimination process (final models). ∗∗ p < .01. ∗∗∗ p < .001 . NS = nonsignificant.

previous studies’ suggestion that sociodemographic characteristics are important determinants of health. Self-esteem and mastery were strongly associated with better health, in particular with mental health and global health measures, thus reconfirming the importance of psychological characteristics for health.

Housing variables were less often significantly associated with health in multivariate analysis. In multivariate analysis, measures of dwelling style (the type of house or flat or the presence of a communal or private garden) were not significant predictors of any health outcome, nor were measures of the status of the dwelling (consumer durables, dwelling value, number of rooms and comparison with other dwellings, home prestige), length of residence, or home autonomy. Housing conditions were only a significant predictor of anxiety. Area conditions, on the other hand, were significantly associated with most health variables. Respondents living in areas in poor condition were more likely to report fair or poor health, more anxiety, and more GP consultations. Turning to the meaning of home, as perceived protection from the home decreased, depression tended to increase. Before the backward elimination process, tenure was not a significant predictor of any of the health outcomes. After the backward elimination process, social renters were more likely than owners to report fair or poor general health and to be depressed.

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This suggests that tenure is a more efficient descriptor than a combination of other housing variables in models of general health and depression.

Thus the most consistent variables in explaining the relationship between tenure and health were personal characteristics: age, self-esteem, and income.

However, housing conditions and home protection were predictors of mental health.

It is worth noting, in particular, that with three of the five health measures, area conditions were more important predictors than were housing characteristics and conditions. Thus the impact of occupying a dwelling may be less significant as a health determinant for many people in modern Britain than the experience of residing in a particular place, comprising one’s home and neighborhood.

Conclusions and Policy Implications We can conclude that the analysis indicates that physical housing conditions and the meaning of home, as well as psychological and sociodemographic personal characteristics, have a role to play in explaining why social renters have worse health than owner-occupiers in the West of Scotland. By revealing the association of various facets of health to both personal and housing characteristics, the present study illustrates how health may inhere to residence—that is, to the particular person in the particular residential environment (Kemeny, 1992). Thus health is determined both by people’s housing as well as the people themselves.

Thus this study illustrates the interconnectedness between a person and his or her environment. Perhaps unconsciously, one’s environment seeps into one’s lived experience and alters one’s self-perception. Cooper (1974) suggests that the “self and house [are] inextricably intertwined as being at some level one and the same thing” (p. 143). Thus a good home may give rise to health-giving feelings of security (Kearns, Hiscock, Ellaway, & Macintyre, 2000).

There are some limitations to our conclusions arising from the study design. The study was cross-sectional and so no causal direction can be determined. It is not possible to tell, for example, whether feeling unprotected in the home causes depression or whether depression causes one to feel unprotected in the home. Additionally all variables were self-reported and it is possible that some of the results could be due to negative affectivity bias. Respondents with a negative approach to life may report both poor health and poor housing although their health might not be worse than others on objective examination.

However, all analyses included self-esteem, which could be seen as a way of controlling in part for negative affectivity. Moreover, the relationship between housing tenure and health was also found by Macintyre, Ellaway, Der, Ford and Hunt (1998) using physical measures taken by a nurse, rather than self-reported measures.

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Another issue arising from the use of a postal survey for data collection is that there were much missing data, particularly on variables such as income. Respondents were more likely to have missing data if they were older or of low socioeconomic status, which may have introduced some further sample biases that are also commonly found in postal surveys.

Our aim in this analysis has been to link epidemiological and housing research through revealing the most important factors that might connect housing tenure and health. We have not looked at how the pathway itself has been structured (for example, which of these variables are mediators, which are moderators, and which are exogenous) and whether other variables may exert an effect through variables in the pathway. This we intend to make the topic of future work on this data set.

Although our results can only suggest possible explanations for the relationship between housing tenure and health for the above reasons, it appears that poor housing conditions in the social rented sector may give rise to anxiety. Also, living in a deprived neighborhood and not feeling protected at home were associated with general poor health and depression.

Some of the extra health problems experienced by social renters are due to their demographic characteristics. Social rented housing was more readily available when older people were forming households than now. If the age profile of those living in social rented housing changes, then the health differential between social renters and owners might also change.

Owner-occupation is only accessible by those with financial resources (see Smith, Easterlow, Munro, & Turner, this issue). Thus, those who occupy social rented accommodation generally have fewer financial resources. Low income is a challenge to health for various reasons (see Gordon & Pantazis, 1997; Shaw, Dorling, Gordon, & Davey Smith, 1999); in some ways we should thus be surprised not to find a health difference between social renters and owners. What is important is whether social rented accommodation itself is as supportive as possible of inhabitants whose health may be fragile.

References Arber, S. (1989). Gender and class inequalities in health: Understanding the differentials. In J. Fox (Ed.), Health inequalities in European countries (pp. 231–249). Aldershot, UK: Gower.

Arber, S., & Cooper, H. (1999). Gender differences in health in later life: The new paradox? Social Science and Medicine, 48, 61–76.

Arber, S., & Ginn, J. (1993). Gender and inequalities in health in later life. Social Science and Medicine, 36, 33–46.

Baker, D. (1997). Inequality in health and health service use for mothers of young children in south west England. Journal of Epidemiology and Community Health, 51, 74–79.

Benzeval, M., & Judge, K. (1996). Access to health care in England: Continuing inequalities in the distribution of GPs. Journal of Public Health Medicine, 18, 33–40.

Best, R. (1996). Successes, failures and prospects for public housing policy in the United Kingdom.

Housing Policy Debate, 7, 535–562.

Health and Housing Tenure

543

Blackman, T., Evason, E., Melaugh, M., & Woods, R. (1989). Housing and health: A case study of two areas in West Belfast. Journal of Social Policy, 18(1), 1–26.

Blaxter, M. (1990). Health and lifestyles. London: Routledge.

Breeze, E., Sloggett, A., & Fletcher, A. (1999). Socioeconomic status and transitions in status in old age in relation to limiting long-term illness measured at the 1991 census. European Journal of Public Health, 9, 265–270.

Carr-Hill, R., Rice, N., & Roland, M. (1996). Socioeconomic determinants of rates of consultation in general practice based on fourth national morbidity survey of general practices. British Medical Journal, 312, 1008–1013.

Cooper, C. (1974). The house as a symbol of self. In J. Lang, C. Burnette, W. Moleski, & D. Vachon (Eds.), Designing for human behavior: Architecture and the behavioral sciences (pp. 130–146).

Stroudsburg, PA:, Dowden, Hutchinson, & Ross.

Dahl, E., & Birkelund, G. (1997). Health inequalities in later life in a social democratic welfare state.

Social Science and Medicine, 44, 871–881.

Department of Health for England and Wales. (1999). Reducing health inequalities: An action report.

London: Her Majesty’s Stationary Office.

Despres, C. (1991). The meaning of home: Literature review and directions for future research and theoretical development. Journal of Architectural and Planning Research, 8(2), 96– 115.

Dew, M. A., Simmons, R. G., Roth, L. H., Schulberg, H. C., Thompson, M. E., Armitage, J. M., & Griffith, B. P. (1994). Psychosocial predictors of vulnerability to distress in the year following heart-transplantation. Psychological Medicine, 24, 929–945.

Dunn, J., & Hayes, M. (2000). Social inequality, population health and housing: A study of two Vancouver neighbourhoods. Social Science and Medicine, 51, 563–587.

Easterlow, D., & Smith, S. J. (1997). Fit for the future? A role for health professionals in housing management. Public Health, 111, 171–178.

Ellaway, A., & Macintyre, S. (1998). Does housing tenure predict health in the UK because it exposes people to different levels of housing related hazards in the home or its surroundings? Health and Place, 4, 141–150.

Faggiano, F., Zanetti, R., & Costa, G. (1994). Cancer risk and social inequalities in Italy. Journal of Epidemiology and Community Health, 48, 447–452.

Filakti, H., & Fox, J. (1995). Differences in mortality by housing tenure and car access from the OPCS longitudinal study. Population Trends, 81, 27–30.

Fogelman, K., Fox, A., & Power, C. (1989). Class and tenure mobility: Do they explain social inequalities in health among young adults in Britain? In J. Fox (Ed.), Health inequalities in European countries (pp. 333–352). Aldershot, UK: Gower.

Fox, A., & Goldblatt, P. (1982). Longitudinal study: Sociodemographic mortality differentials. London: Office of Population and Census Statistics.

Goldman, N., Korenman, S., & Weinstein, R. (1995). Marital status and health among the elderly.

Social Science and Medicine, 40, 1717–1730.

Gordon, D., & Pantazis, C. (1997). Breadline Britain in the 1990s. Aldershot, UK: Ashgate.

Gould, M. I., & Jones, K. (1996). Analyzing perceived limiting long-term illness using UK Census microdata. Social Science and Medicine, 42, 857–869.

Gurney, C. (1999). Pride and prejudice: Discourse of normalisation in public and private accounts of home ownership. Housing Studies, 14, 163–183.

Hiscock, R. (2001). The relationship between housing tenure and health: Does ontological security play a role? Unpublished doctoral dissertation, MRC Social and Public Health Sciences Unit, University of Glasgow, Scotland.

Hunt, S., & McKenna, S. (1992). The impact of housing quality on mental and physical health. Housing Review, 41, 47–49.

Ineichen, B. (1993). Homes and health: How housing and health interact. London: E & FN Spon.

Johansson, L. M., Sundquist, J., Johansson, S. E., Qvist, J., & Bergman, B. (1997). The influence of ethnicity and social and demographic factors on Swedish suicide rates—A four year follow-up study. Social Psychiatry and Psychiatric Epidemiology, 32, 165– 170.

544

Hiscock, Macintyre, Kearns, and Ellaway

Kearns, A., Hiscock, R., Ellaway, A., & Macintyre, S. (2000). “Beyond four walls.” The psycho-social benefits of home: Evidence from West Central Scotland. Housing Studies, 15, 387–410.

Kemeny, J. (1992). Housing and social structure: Towards a sociology of residence (Working Paper 102). Bristol, UK: School for Advanced Urban Studies, University of Bristol.

Kogevinas, E. (1990). Longitudinal study: Sociodemographic differences in cancer survival. London: Office of Population and Census Statistics.

Leon, D., & Wilkinson, R. (1989). Inequalities in prognosis: Socio-economic differences in cancer and heart disease survival. In J. Fox (Ed.), Health inequalities in European countries (pp. 250–300).

Aldershot, UK: Gower.

Lowry, S. (1991). Housing and health. London: British Medical Journal.

Macfarlane, A., & Mugford, M. (1984). Birth counts: Statistics of pregnancy and childbirth. London: Her Majesty’s Stationary Office for National Perinatal Epidemiology Unit (in collaboration with the Office of Population Censuses and Surveys).

Macintyre, S. (1986). The patterning of health by social position in contemporary Britain; directions for sociological research. Social Science and Medicine, 23, 393–415.

Macintyre, S., Ellaway, A., Der, G., Ford, G., & Hunt, K. (1998). Do housing tenure and car access predict health because they are simply markers of income and self esteem? A Scottish study.

Journal of Epidemiology and Community Health, 52, 657–663.

Macintyre, S., Ellaway, A., Hiscock, R., Kearns, A., & Der, G. (2002). What features of the home and the area might help to explain observed relationships between housing tenure and health?

Evidence from the West of Scotland. Manuscript submitted for publication.

Macintyre, S., Hiscock, R., Ellaway, A., & Kearns, A. (2000). Housing tenure and car ownership: How do they contribute to inequalities in health? In H. Graham (Ed.), Understanding health inequalities (pp. 129–142). Buckingham, UK: Open University Press.

Macintyre, S., Hiscock, R., Kearns, A., & Ellaway, A. (2001). Housing tenure and car access: Further exploration of the nature of their relationships with health in a UK setting. Journal of Epidemiology and Community Health, 55, 330–331.

MacLeod, M. D., Graham, E., & Johnston, M. (2001). Relative deprivation and recovery from first acute myocardial infarction. Research findings from the Health Variations Programme 8. Lancaster, UK: Economic and Social Research Council.

Madigan, R., & Munro, M. (1991). Gender, house and home−Social meanings and domestic architecture in Britain. Journal of Architectural and Planning Research, 8, 116–132.

Mann, S., Wadsworth, M., & Colley, J. (1992). Accumulation of factors influencing respiratory illness in members of a national birth cohort and their offspring. Journal of Epidemiology and Community Health, 46, 286–292.

McCarthy, P., Byrne, D., Harrison, S., & Keithley, J. (1985). Housing type, housing location and mental health. Social Psychiatry, 20, 125–130.

Moser, K., Pugh, H., & Goldblatt, P. (1988). Inequalities in women’s health: Looking at mortality differentials using an alternative approach. British Medical Journal, 296, 1221–1224.

Pearlin, L., & Schooler, C. (1978). The structure of coping. Journal of Health and Social Behaviour, 19, 2–21.

Pell, J., McMahon, A., Walsh, D., Boyd, J., Gemmell, I., MacIntyre, C., Morrison, C., & Walker, A. (1999). Study of the association between housing condition and health: Final report to Scottish Homes. Edinburgh, UK: Scottish Homes.

Penninx, B., Beekman, A. T. F., Ormel, J., Kriegsman, D. M. W., Boeke, A. J. P., Vaneijk, J. T. M., & Deeg, D. J. H. (1996). Psychological status among elderly people with chronic diseases−Does type of disease play a part? Journal of Psychosomatic Research, 40, 521–534.

Phillimore, P., Beattie, A., & Townsend, P. (1994). Widening inequality of health in Northern England, 1981–91. British Medical Journal, 308, 1125–1128.

Pieda (1996). Third survey of consumer preference in housing. Edinburgh, UK: Scottish Homes.

Rainwater, L. (1966). Fear and house-as-haven in the lower class. Journal of the American Institute of Planners, 32, 23–31.

Rogerson, P. (2001). Statistical methods for geography. London: Sage.

Rosenberg, M. (1965). Society and the adolescent self image. Princeton, NJ: Princeton University Press.

Health and Housing Tenure

545

Rosenberg, M., Schooler, C., Schoenbach, C., & Rosenberg, F. (1995). Global self-esteem and specific self-esteem−Different concepts, different outcomes. American Sociological Review, 60(1), 141–156.

Saunders, P. (1989). The meaning of “home” in contemporary English culture. Housing Studies, 4, 177–192.

Scottish Office Department of Health. (1997). Scottish Health Survey 1995, 1. The Stationary Office, Edinburgh, Scotland.

Seilheimer, T., & Doyal, G. (1996). Self efficacy and consumer satisfaction with housing. Community Mental Health Journal, 32, 549–559.

Shaw, M., Dorling, D., Gordon, G., & Davey Smith, G. (1999). The widening gap: Health inequalities and policy in Britain. Bristol, UK: Policy Press.

Sloggett, A., & Joshi, H. (1994). Higher mortality in deprived areas: Community or personal disadvantage? British Medical Journal, 309, 1470–1474.

Sloggett, A., & Joshi, H. (1998). Indicators of deprivation in people and places: Longitudinal perspectives. Environment and Planning A, 30, 1055–1076.

Somerville, P. (1998). Explanations of social exclusion: Where does housing fit in? Housing Studies, 13, 761–780.

Sundquist, J., & Johansson, S.-E. (1997). Self reported poor health and low educational level predictors for mortality: A population based follow up study of 39156 people in Sweden. Journal of Epidemiology and Community Health, 51, 35–40.

Thomson, H., Petticrew, M., & Morrison, D. (2001). Housing improvement and health gain: A summary and systematic review (Occasional Paper No. 6). Glasgow, UK: MRC Social & Public Health Sciences Unit.

Townsend, P., & Davidson, N. (Eds.). (1988). The Black Report. London: Penguin.

U.S. Department of Commerce. (2001). Census of population and housing, 2000. Washington, DC: Author.

Watson, D., & Pennebaker, J. (1989). Health complaints, stress and distress: Exploring the central role of negative affectivity. Psychological Review, 96, 234–254.

Zigmond, A., & Snaith, R. (1976). The Hospital Anxiety and Depression Scale. Acta Psychiatrica Scandinavica, 67, 361–370.

ROSEMARY HISCOCK is a researcher at Family Medicine Stockholm, which is part of the Karolinska Institut, Sweden. She has recently completed a Ph.D. at the University of Glasgow. Her main research interests are health inequalities, housing and neighborhoods, and the influence of psychosocial factors.

SALLY MACINTYRE, Ph.D., is Professor and Director of the MRC Social & Public Health Sciences Unit at the University of Glasgow. She was awarded her Ph.D. at Aberdeen University, Scotland, and has worked for many years on social patterning of health by socioeconomic position, area of residence, and gender. She is Editor-in-Chief of the international journal Social Science and Medicine.

ADE KEARNS is Professor and Head of the Department of Urban Studies at the University of Glasgow. He is a graduate of Cambridge University with a degree in Geography. His research interests are in the following: neighborhood change and social processes, the health and well-being impacts of housing and residence, low demand and unpopular housing, and public space and the public realm.

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ANNE ELLAWAY is a researcher in the Medical Research Councilâ&#x20AC;&#x2122;s Social and Public Health Sciences Unit based at the University of Glasgow in Scotland. Research work includes exploring the processes by which place of residence might influence health and the ability to lead healthy lives. Published work includes the role of housing and neighborhood conditions in producing health outcomes.