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Housing related difficulties, housing tenure and variations in health status: evidence from older people in Wales
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Health & Place 12 (2006) 267–278 www.elsevier.com/locate/healthplace
Housing related difficulties, housing tenure and variations in health status: evidence from older people in Wales Gillian S. Windlea,, Vanessa Burholta, Rhiannon T. Edwardsb a
The Centre for Social Policy Research and Development, The Institute of Medical and Social Care Research, University of Wales, Bangor, Ardudwy, Holyhead Road, Bangor, Gwynedd, Wales LL57 1PX, UK b The Centre for the Economics of Health, The Institute of Medical and Social Care Research, University of Wales, Bangor, UK Accepted 1 August 2004
Abstract This study aimed to examine housing-related difficulties, the relationship with housing tenure and the subsequent influences on health status in a population sample of older people in Wales. Comparisons with health status normative data were undertaken to determine any geographical differences. A random sample of respondents were interviewed in their own homes (N ¼ 423). Data included demographic information, self-reported health status, housing problems, tenure and factors relating to energy efficiency. Univariate analysis found that owner occupiers reported the least housing difficulties and the best health status. Those in public rented properties experienced the most difficulties and the poorest health. The health status of the sample was generally poorer than the norms. Multivariate analysis found that housing difficulties, being cold with current heating and hours spent at home predicted poorer health status. This suggests that characteristics of the home environment may help to explain the differences between tenure and health. Considerable financial outlay may be required to meet policy initiatives that support older people remaining independent, autonomous and able to ‘age in place’. r 2005 Elsevier Ltd. All rights reserved. Keywords: Older people; Independence; Housing conditions; Self-reported health; Housing tenure; Wales
Introduction Housing has been described as the foundation of social care (National Housing Federation, 1999; Harrison and Heywood, 2000) and is highlighted in the Framework for a National Housing Strategy for Wales as being an important factor in the successful delivery of ‘community care’ especially for older people wishing to remain in their own homes (National Consultative Forum on Housing in Wales, 1999). The importance Corresponding author. Tel.: +44 1248 383968; fax: +44 1248 382229. E-mail address: [email protected] (G.S. Windle).
of housing is further reinforced in the United Nation’s International Plan of Action on Ageing (2000) which states ‘suitable housing is even more important for the elderly, whose abodes are the centre of virtually all of their activities’. This paper reports some of the findings from a study entitled Housing for an Ageing Population: Planning Implications (HAPPI). HAPPI was designed to provide evidence on housing needs and preferences to inform policy decisions and address many of the requirements of the National Assembly for Wales. The objectives here were to examine housing difficulties, their relationship
1353-8292/$ - see front matter r 2005 Elsevier Ltd. All rights reserved. doi:10.1016/j.healthplace.2004.08.010
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Table 1 The links between housing and health Author and date
Housing problem
Health problem
Strachan and Elton, 1986 McCarthy et al., 1985 Packer et al., 1994
Damp and mould Poor ventilation
Asthma and Respiratory illness
Collins et al, 1985 Collins, 1986, 1987 Age Concern, 2001
Cold temperatures & Lack of efficient heating
Respiratory illness Rise in blood pressure Hypothermia
Birtchnell et al., 1988 Hopton and Hunt, 1996
General poor quality
Depression Depression and anxiety
Macintyre et al, 1998 Ellaway and Macintyre, 1998
with housing tenure and the influences on the health status of a population sample of older people in Wales. It has been estimated that older people spend between 70% and 90% of their time in their home (Baltes et al., 1990, Czaja, 1988, Gabb et al., 1991), therefore, an appropriate living environment should be considered crucial to maintain and/or enhance independent living (The Royal Commission on Long Term Care, 1999). Retaining independence and autonomy are recognised as being crucial for maintaining quality of life, underpinning policy and practice (UN/Division for Social Policy and Development, 2000, Welsh Assembly Government, 2003). There is considerable evidence suggesting that poor quality housing can have an adverse effect on the health of its occupants (see Table 1), recently confirmed in a systematic review of the literature (Thompson et al., 2002). For older people, health is widely acknowledged as one of the key elements of the ageing process (e.g. Siddell, 1995, Wenger et al., 2001). Findings from a longitudinal study show that the most salient life domain for older people is reported to be health and the maintenance of mobility (Wenger et al., 2001). Yet health and mobility difficulties can be exacerbated by an inappropriate home environment, affecting the ability to manage at home, which subsequently can impact on independent living (The Royal Commission on Long Term Care, 1999; The Office for National Statistics, 1999), and well-being (Lawton, 1989). Accidents, in particular falls are among the commonest causes of death and disability in older people (Effective Health Care, 1996). In total, 40% of fatal accidents occur in the home and 85% of these involve people over the age of 65 (Effective Health Care, 1996). The ability to heat the home is imperative, as the older population are far more susceptible to the
Limiting longstanding Illness
effects of cold temperatures (Environmental Epidemiology Unit, 1999). A number of UK studies have found that houses occupied by older people are slightly colder than average (Collins, 1993) and the Welsh House Condition Survey (National Assembly for Wales, 2001a) found that older people were less likely to live in a home with central heating. The absence of central heating is considered to be an indicator of housing deprivation (National Assembly for Wales, 2000). It could be argued that difficulties experienced at home by some older people are related to their functional status, and not necessarily a reflection of the condition of the property. On the other hand, if functional limitations are exacerbated by inappropriate housing conditions, then some occupants could face an increased risk of a poor health outcome. Previous research has identified that Wales has a relatively high level of ill health, and the health of the Welsh population as measured by life-expectancy and long term limiting illness is worse than the UK average (Acute Services Development Group, 2000). It is not being suggested here that these high levels of ill health are purely a consequence of poor housing however there are a number of factors relating to housing in Wales that are indicative of potential health risks. Poor and unfit housing is often associated with the age of the property, with older properties more likely to be classed as unfit (Leather et al., 1994; National Assembly for Wales, 2001a). The Welsh housing stock is older and in worse condition than in England: 8.5% of the housing stock was rated as unfit for habitation in 1999, which is above the level in England (National Consultative Forum on Housing in Wales, 1999). The 1998 Welsh House Condition Survey found that 14.9% of dwellings built before 1919 were unfit for habitation compared to 2.4% built after 1964. In Gwynedd (the study area), 48% of the housing stock was constructed before 1919 of which
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17% was class as unfit1 (National Assembly for Wales, 2001a). Housing quality varies further when examined by tenure. The highest proportions of unfit houses are in the private rented sector (Department of the Environment and Transport and the Regions, 2000). In Wales, research has demonstrated that 11.9% of owner occupied houses; 25.5% of private rented houses; 15.8% of LA rented houses and 6% of housing association rented houses were considered unfit. With the exception of the housing association houses these levels were consistently higher that the proportions of unfit housing in England (5.5% owner occupied; 20.5% private rented; 6.9% of LA rented and 6.7% of housing association) (Leather and Morrison, 1997). Housing tenure is also associated with the age of occupants. The majority of older people are owneroccupiers (Office for National Statistics, 1999). Analysis of the General Household Survey demonstrated that in the age group 65–74, 66% were owner occupiers and owned their properties outright in comparison with 19% of the 45–54 age group. Wales has the largest proportion of home ownership in the UK (72%) and older home owners are more likely than other households to live in properties built before 1919 and least likely to live in properties built after 1965 (Hancock et al., 1999), potentially increasing the likelihood of their homes being of poorer quality. Poor quality housing in the UK has been found to be disproportionately occupied by single older people (Leather and Morrison, 1997). These properties tended to be older and in the private rented sector (Leather and Morrison, 1997). The Welsh House Condition Survey also found that the highest proportion of unfit properties in the owner occupied sector (12.2%) and in the private rented sector (25.7%) belonged to single people of a pensionable age. Older people in Wales may then have an increased chance of health risks from their properties, which may vary by tenure. Variations in health status and mortality have been linked with housing tenure (owner occupied, or rented property). Home ownership is often found to be an independent predictor of better general health status (Thompson et al., 2002). Conversely, it has been found that living in rented property is associated with low health-related quality of life and low self-reported health status (Kind et al., 1999). A longitudinal study has found that living in rented property is associated with higher death rates compared to home-ownership. 1
The fitness standard (Housing Act 1989) states that a dwelling should meet a number of requirements, e.g.: be free from disrepair and damp, have adequate provision for lighting, have, for exclusive use of the occupants a bath or shower and a wash basin with hot and cold water, have adequate facilities for food preparation and adequate provision for heating and ventilation.
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Mortality was 26% higher for male and 21% higher for females renting local authority properties than owners during 1971–1981. In the following period (1981–1989) the excess mortality among those renting was 22% for males and 32% for females (Filakti and Fox, 1995). In Scotland a population sample survey found that living in council rented accommodation, compared to living in private rented accommodation or being an owner-occupier, has been independently associated with ratings of both significant and severe chronic pain that had persisted for at least 3 months (Smith et al., 2001). The reasons why housing tenure might determine variations in health status have until recently been given little attention (Ellaway and Macintyre, 1998). One suggestion is that the variation in health status for housing tenure reflects the socio-economic status of its occupants. Home-ownership is often regarded as an indicator of financial wealth, and socio-economic status is strongly related to health status (Harding et al., 1997). The notion that housing tenure predicts health status as it represents socio-economic status was examined by Macintyre et al. (1998). Using data from two adult cohorts in Scotland these authors found that home ownership was a predictor of better health even when factors such as income were controlled for. They concluded that health may vary perhaps because there were health promoting or health damaging factors in the properties across different housing tenures, these being the least problematic in owned properties. Building on this finding Ellaway and Macintyre (1998) hypothesised that aspects of tenure (housing conditions and quality of the surrounding environment) could be associated with health, independent of income or social class. A survey of 318 40 year olds and 373 60 year olds in Scotland provided data on tenure and a number of potential housing stressors, such as damp or condensation, cold properties and noise. Their analysis suggests that poor housing and poor quality local environment contributed to poor health, independent of income. Thus, the quality of the housing stock across tenure groups may expose people to a home environment that can have a detrimental effect on their health. Considering that house conditions can impact on health outcomes, appropriate housing for older people is clearly important. Within Wales there is more poor quality housing than the rest of the UK and the quality of the housing stock varies across housing tenure. Given the increased likelihood that as proportionally more older people live in poor quality housing they may experience housing-related difficulties, this paper aimed to examine whether health variations across housing tenure were due to housing-related difficulties. In line with the literature, it was hypothesised that:
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1. Respondents in private rented accommodation would experience the most problems, whilst owner occupiers would experience the least. 2. Owner occupiers would report the best health status, those in rented accommodation the poorest. As there are differences between Wales and the rest of the UK for health status and housing quality, the third hypothesis was that: 3. The study sample would have poorer health than UK population norms when examined across housing tenure. Finally a model was constructed to determine the independent influences of the variables on health status. In line with the literature it was hypothesised that: 4. Characteristics of the home environment may help to explain differences in health between tenure groups. Housing difficulties would independently predict poorer health, irrespective of tenure.
Method Sampling The sample for HAPPI was selected from the county of Gwynedd in North Wales to provide a representative sample from a diverse range of areas. These were a dispersed farming community, a retirement destination, an ex-quarrying community, an urban area, a concentration of difficult to let sheltered housing, and a market town. In order to identify the appropriate age group and to achieve a random sample, a door-to-door census of occupied households in the chosen communities was conducted. Electoral rolls for the areas were obtained containing a total of 8098 names and addresses. Addresses were entered onto a census sheet for interviewers to record occupants’ details. Interviewers were instructed to also call at any unlisted properties in the areas to ensure that the final sample would be as representative as possible of the locality. Information was obtained on the occupants’ age, gender and preferred language of interview (English or Welsh). Potential respondents (aged 70 or over) were entered onto a database. Random sampling procedures were used to draw a proportional sample from each community. These were 8% for the dispersed farming community, 27% for the retirement destination, 12% for the exquarrying community, 8% for the urban area, 20% for the area with difficult to let sheltered housing, and 24% for the market town. The smaller sample from the urban area was due to the large proportion of students in this ward.
Interviewing Interviewers were trained by the research team. Guidelines for professional conduct and ethical considerations were circulated to the interviewers prior to the meeting and were reiterated at the training sessions. After training, interviewers understood the necessity of obtaining consent from interviewees, issues regarding confidentiality, contact with respondents and the confounding affect from the presence of other family members or friends during the interview session. English and Welsh versions of the questionnaire were used by the interviewers. The former North Wales Health Authority was responsible for front-back translation and calibration of items in order to represent the intent of the questionnaire items within the cultural context. Respondents selected for inclusion in the sample were sent a letter describing the study and indicating when an interviewer might call. Respondents were asked to contact the Principal Investigator if they did not wish to take part in the study. Interviewers called at the home of the respondents to obtain an interview, or to make appointments for a convenient date. Welsh speaking interviewers were matched with Welsh speaking respondents. Administering the questionnaire took place in the respondents own home in the form of a structured faceto-face interview. Interviewing took place between September 2001 and February 2002. The final sample size was 423, representing a response rate of 54% of those identified in the census and randomly selected for interview. A high proportion (19%) refused to be interviewed, 12% refused as they were too ill, 8% could not be contacted, and 7% refused for other reasons, such as they were not residents of the area (holiday property). The project target initially was 500. This number was decided on so as to be powerful enough to enable planned complex statistical modelling to be performed. However, responses dropped during the course of the data collection. Feedback from interviewers suggested that potential respondents were concerned about allowing interviewers into their homes, due to a brutal murder of a local older woman. Interviews were halted to avoid causing any unnecessary anxiety. The final sample was felt to be sufficient to undertake the analysis.
Measures General health Although the literature demonstrates a wide variety of health outcomes as a result of poor housing, for the purpose of this analysis a simple measure of self-assessed health was used. Such measures have been demonstrated to be strong predictors of mortality (Office for National Statistics, 1999).
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Respondents’ assessed their own health state on the self-rated Visual Analogue Scale (EQ-VAS) ranging from 0 (worst health state) to 100 (best state). This scale is part of the EuroQoL EQ-5D health state classification, and was included in the study for (a) its simplicity, (b) it enabled comparison with population norms and c) the purpose of some planned economic analysis. The authors of the EQ-5D state it is a reliable measure of health status and it is used across a wide range of settings (Brooks, 1996). It is advocated as an easy to use measure, making it a potentially popular choice for use with older people (Brooks, 1996). The scale was enlarged so as to be visible to respondents’ with poor eyesight. Respondents’ were asked to mark on the scale where they viewed their health state today. (Fig. 1).
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Population norms for the EQ-VAS derived from a sample of 3395 respondents are available for the UK (Kind et al., 1999). This normative data was obtained from a survey designed to collect data on health state valuations and self-reported health using the EuroQoL EQ-5D questionnaire. The sample was representative of the population with respect to gender, age and social class. Of the total sample 547 were aged 70 and over with a mean age of 76.5. Comparisons were drawn between the health status of the HAPPI sample and the population norms across the housing tenure categories. For the HAPPI sample the respondents’ ages were recoded into two groups, 70–74 and 75+ in order to match the normative data.
Your own health state today
To help people say how good or bad a health state is, we have drawn a scale (rather like a thermometer) on which the best state you can imagine is marked 100 and the worst state you can imagine is marked O.
Best imaginable health state 100
9 0
We would like you to indicate on this scale how good or bad your own health is today, in your opinion. Please do this by drawing a line from the box below to whichever point on the scale indicates how good or bad your health state is.
8 0
7 0
6 0
Your own health state today
5 0
4 0
3 0
2 0
1 0
0
Worst imaginable health state Fig. 1. EQ-5D Visual Analogue Scale (EQ-VAS).
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Housing It was not financially possible to undertake full structural surveys of the respondents’ properties, however respondents were asked questions relating to problems experienced with aspects of their homes. These related to aspects of the home environment that might enhance, maintain or have a negative impact on health status. Questions relating to difficulties that could be exacerbated by reduced physical functioning, such as difficulties with steps and stairs were also examined. Two questions were asked regarding warmth in their homes that were coded dichotomously (no/yes). ‘‘On the whole, during cold spells, are you warm in your home with the heating you use, without wearing extra clothing?’’ ‘‘During cold spells, are you warm in bed without wearing extra clothing or using an electric blanket?’’ Respondents were asked whether they had difficulties with items such as steps/stairs, heating, damp/condensation, draughts and difficulties using a bath/shower (see Table 3 for items). The answers were coded dichotomously (yes/no). For the purpose of multivariate analysis all of the ‘difficulty’ questions were collapsed together to give a continuous scale. Higher scores indicate poorer condition and more difficulties (range between 0 and 14). The reliability of the scale (Cronbach’s Alpha) was 0.62. There is some debate as to the acceptable level for good internal consistency, ranging 40.50 (Cronbach, 1951) to 0.70 (Nunally, 1978). In this instance 0.62 was felt to be sufficiently acceptable for analysis. The age that the property was built was recorded and whether the respondents had roof or loft insulation and central heating. The latter two items were included as they are used as indicators of poor housing in the Welsh Index of Multiple Deprivation (National Assembly for Wales, 2000). Respondents also provided information on the average amount of time they spent in their homes per day (24 h) and how long they had lived in their properties. Respondents indicated the tenure of their homes (owner-occupier, owned by child or other relative, rented from the local authority, rented from a housing association or privately rented). The normative data for housing tenure is categorised as owner/mortgage, private rented, public rented and other. The HAPPI questionnaire gained more detail on housing tenure than the EQ normative data categories. To make the comparisons with the norms the HAPPI data for owner occupier and child or other relative were combined to reflect the category owner/mortgage in the EQ norms. The categories ‘local authority rented’ and ‘housing association rented’ were combined to reflect the category
public rented in the EQ norms. Private rented remained the same. The category ‘other’ was excluded as the HAPPI sample contained data for only one respondent, and for four respondents in the normative data, which are not sufficient for parametric analysis. General demographic data (age, gender, marital status and income) were also obtained.
Analysis The relationship between the individual housing difficulties and tenure were examined by cross-tabulations to determine the proportions experiencing difficulties in each tenure group, and the Spearman Chi Square test to determine if any differences between tenures are significant. Independent sample t-tests were used to determine differences in health status between the HAPPI sample and the population norms across the housing categories, as this is the recommended procedure in the population norms handbook (Kind et al., 1999). The unequal sample sizes across the tenure groups suggested that the equality of variance assumption for parametric analysis may be violated. To determine differences in self-reported health and housing difficulties between the tenure categories, one way ANOVA’s were run first and the Levene test for equality of variance computed. This was not significant for selfreported health, but significant for housing difficulties. A Kruskal–Wallis test was used for the housing difficulties analysis. To determine the independent influences of the variables on health, a hierarchical multiple regression model was developed with selfreported health status as the dependent variable.
Results Four respondents were excluded from this analysis as their scores on the EQ-VAS were difficult to interpret, and five refused to answer, leaving a final sample of 411 for the analysis. The age of the respondents’ ranged from 70 to 99, with the mean age being 78 (standard deviation ¼ 5.55). Fifty nine per cent were female and 41% male. 52% were married, 7% single, 37% widowed and 4% were divorced. 41% lived alone. The mean selfreported health score of the whole sample was 70.40 (standard deviation ¼ 18.71). In total, 79% (n ¼ 333) of the respondents fell into the owner/mortgage category, 18% (n ¼ 72) lived in public rented properties and 3% (13) in private rented properties. In total, 40% of the respondents lived in housing built in or before 1919. The majority (85%) had lived in their houses for 6 or more years, and 33% of these had lived there for 30 or more years. Few respondents lacked essential amenities such
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as hot water (n ¼ 3), an inside flush toilet (n ¼ 4), or cooking facilities (n ¼ 4). Respondents in this study spent an average of 19.97 h (s.d. 4.1) in their homes. This is equivalent to an average of 83% of the day spent at home. Nineteen per cent reported that during cold spells they were not warm in their homes without having to wear extra clothing. Of these, 65% were owners, 28% public renters and 6% private renters. Twenty four per cent reported that during cold spells they were not warm in bed without wearing extra clothing or using an electric blanket. Of these 72% were owners, 23% public and 5% private renters. Just over a third of the respondents (38%) had no central heating and 17% had no roof or loft insulation. Of those who reported their weekly income, 56% had £140 per week or less (see Table 2). Table 3 shows the proportion of the respondents that reported difficulties with their housing. Those in rented accommodation tended to report more problems than those who owned their homes, although there were some differences between the types of rented tenure. When the individual items were collapsed together, there was a significant difference in the number of housing problems between the tenure groups (H ¼ 9.82, 2, po0.01). Owner occupiers had the lowest average scores (m ¼ 0.94/mean rank ¼ 199.49) indicating the fewest difficulties followed by those in private rented properties (m ¼ 1.64/mean rank ¼ 231.71) whilst those
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Table 3 Proportions reporting difficulties Problems with
Steps/stairs Floor covering Heating*** Damp/ condensation** Draughts*** Lighting*** Noise* Decoration* Repairs Lack of facilities** Size of dwelling Difficulty using bath/shower Difficulty using WC Security** Outside access
Owneroccupier
Tenure Public rented
Private rented
17.0 1.0 5.0 7.0
17.0 1.0 17.0 19.0
0.0 0.0 14.0 22.0
7.0 1.0 5.0 8.0 15.0 1.0 5.4 11.0
26.0 1.0 13.0 16.0 20.0 0.0 7.1 16.0
14.0 14.0 7.0 21.0 22.0 14.0 0.0 14.0
2.0 1.0 7.0
4.0 10.0 4.0
7.0 7.0 7.0
*po0.05. **po0.01. ***Po0.001.
in public rented had the highest average scores (m ¼ 1.71/mean rank ¼ 243.51). Table 2 Income
Tenure and health
Weekly income (£ sterling)
Frequency
Percentage
0–69.99 70–79.99 80–89.99 90–99.99 100–119.99 120–139.99 140–159.99 160–179.99 180–199.99 200–219.99 220–239.99 240–259.99 260–279.99 280–299.99 300–319.99 340–359.99 360–379.99 380–399.99 400+ Total Missing Total
19 35 15 27 45 21 26 20 16 11 6 9 7 8 6 2 1 2 13 289 130 419
6.6 12.1 5.2 9.3 15.6 7.3 9.0 6.9 5.5 3.8 2.1 3.1 2.4 2.8 2.1 0.7 0.3 0.7 4.5
There was a significant difference in the self-reported health status of respondents’ by housing tenure (F ¼ 4.90, 407, po0.01). Owners reported the best health score (m ¼ 71.81), followed by those in private rented (m ¼ 66.15) whilst those in public rented reported the worst score (m ¼ 64.39). Post hoc analysis (Tukeys HSD) found the largest difference (m ¼ 7.42) was between owner occupiers and respondents in public rented accommodation. Comparison with population normative data Fig. 2 presents the mean self-reported health score for respondents aged 70–74 years (n ¼ 134) compared to the UK population norms (n ¼ 219). In comparison to the population norms, our sample of owner occupiers and those living in private rented accommodation had lower self-reported health scores. An independent sample t-test found the difference between the self-reported health status of the owner occupiers in the HAPPI sample to be significantly less
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90 HAPPI NORMS
85 78.7
Mean score
80 75
Predictors
75
1
67.6
65 60 55 50 Owner
Private rented
Public rented
Fig. 2. Self-reported health: 70–74 age group.
90 HAPPI NORMS
85 78.58
Mean score
80
Self-reported health status
72.2 71.8
71.2
70
75
Table 4 Regression of housing variables on health status. Standardised coefficients of included variables
72.5
71.82
3
b
b
0.29 0.07 0.06
0.01 0.06 0.03
0.16* 0.06 0.04 0.003
0.05
0.22*** 0.02 0.17* 0.08 0.77 0.14* 0.15
*po0.05 ***po0.001.
67.58
70
b Control variables Gender 0.03 Age 0.09 Income 0.09 Housing tenure Public rented Private rented Housing problems Difficulties scale Cold in bed Cold with current heating Pre-1919 No roof/loft insulation Average number of hours at home 0.02 Changes in r2
2
64.5
65
61.42
60
Multiple regression model
55 50 Owner
Private rented
Public rented
Fig. 3. Self-reported health: 75+ age group.
than the population norms (t ¼ 4:76; df ¼ 239; po0.01). Owing to the low frequency for the category private rented (n ¼ 7) no statistical tests were performed. For respondents in public rented properties there were no significant differences in the self-reported health status between HAPPI the sample and the population norm. Fig. 3 shows the corresponding self-reported health status by housing tenure for respondents aged 75 years and over in the HAPPI sample (n ¼ 275) and the normative data (n ¼ 302). The figure shows that both the HAPPI sample and population norms follow the expected pattern, with owner occupiers reporting better health than those in either private or public rented housing. For each housing category, the self-reported health status of the respondents in the HAPPI sample is lower than national norms. This difference was statistically significant for owner occupiers (t ¼ 3:94; df ¼ 362; po0.01) and those living in public rented accommodation (t ¼ 2:03; df ¼ 181; po0.05). No statistical test was undertaken for those respondents living in the private rented sector due to the small sample size for this group (n ¼ 6).
Predictor variables were entered into the model in blocks. The improvement in the explanatory power of the model was assessed for each block of variables. The first block consisted of demographic factors (age, gender, income). The second block of variables included the three housing tenure categories (owner, private rented and public rented). The third block contained the housing-related problems (housing difficulties scale, whether or not property was built in or before 1919, whether during cold spells respondents are warm at home with the heating used without wearing extra clothing, whether or not during cold spells respondents were warm in bed without wearing extra clothing or using an electric blanket, the average number of hours spent at home each day and whether or not respondents had roof or loft insulation and central heating). Table 4 summarises the results of the stepwise regressions. The coefficients for the variables excluded during the running of the analysis are not reported. Without including the housing problems living in public rented accommodation predicts poorer selfreported health. When the housing problems are included, controlling for age, gender and income, housing tenure is no longer significant whilst more housing-related difficulties, feeling cold at home with current heating and more hours spent in the home predicted poorer health status.
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Discussion The aim of this study was to examine housing difficulties, their relationship with housing tenure and the influences on the health status of a population sample of older people in Wales. The first hypothesis was partially supported. Owner occupiers experienced the least problems, which was predicted from the literature. Respondents in private rented accommodation had more difficulties than owner occupiers, but it was respondents in public rented accommodation who had the highest number of difficulties. This finding may be partially explained considering that within Wales there is a substantial backlog of at least £750 million of improvements and repairs that are needed in this sector (National Assembly for Wales, 2001b), suggesting that the housing quality in this tenure group is particularly poor. The second hypothesis was supported: owner occupiers reported the best health status. In addition, respondents in public rented and private rented housing both reported health scores below the sample mean, whilst owner occupiers were higher than the sample mean. This finding supports other research where owner occupiers have better health (Thompson et al., 2002), and renters have poorer health (Kind et al.,1999; Smith et al., 2001). There were also differences between the health status of our sample and the UK population norms. These findings suggest that the health status of the HAPPI older population sample, particularly the oldest cohort (75+), is worse than the UK population norms when examined by housing tenure. It is difficult to infer that the poorer health status within this sample of older people, in comparison to the normative data, was purely a consequence of housing. A clear factor limiting any generalisability of these results was the design. Crosssectional designs, such as that employed in this study, can be confounded by the effects of past health behaviours (Carr-Hill, 2000; Marsh et al., 1999). A longer time period to study the effects of poor housing would determine the effects on health more accurately (Barrow and Bachan, 1997). Also, this is a post hoc analysis undertaken on data obtained from a larger study. Consequently, the sample sizes within the tenure groups are unequal, and are quite small for those in private rented accommodation. Despite the limitations of the design the research literature provided some underlying evidence for the differences found in this study in the context of our hypotheses. Specifically, within Wales there is more poor quality housing across all tenure groups than the rest of the UK, which is disproportionately occupied by older people. Likewise the health of the Welsh population as measured by lifeexpectancy and long-term limiting illness is worse than the UK average (Acute Services Development Group,
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2000). Although the literature provided some explanation, the link found between tenure and health was fairly descriptive, and required some further exploration. It was the purpose of the final hypothesis (that health variations across housing tenure reflect housing-related difficulties), to provide some evidence for a possible mechanism to assist in explaining the differences. The first step of the regression model demonstrated that living in public rented accommodation predicted lower health status. However, when the housing variables were entered, it was respondents who experienced the most problems, who were cold in their home with their current heating and spent the most time in their home that had the lowest self-reported health status, irrespective of housing tenure. This suggests that the initial finding for variations in health status by housing tenure may actually reflect difficulties experienced in the properties in these tenure groups. That is, the home environment may be influencing health. The results of the analyses are generally in line with those of Ellaway and Macintyre (1998) who also found that housing tenure affected health because aspects of the home environment had an adverse affect on health. It should be noted that the significant prediction of poor health by spending long periods in the home could also be due to becoming housebound through poor health. However, this in itself could further increase the risk to health if the person was experiencing difficulties with their properties. Of particular concern is proportion (19%) of the sample that stated they were cold in their homes with their current heating without having to wear extra clothing. The average time spent at home each day was also high for the respondents and 38% of this sample had no central heating, potentially increasing their risk of hypothermia. Each year in Britain at least 30,000 people aged over 65 die as a consequence of winter conditions (Help The Aged, 1994). One study found that excess winter deaths-related to dwellings with low energy efficiency ratings and low indoor temperatures (Wilkinson et al., 2001). Attending to the heating conditions in the homes of older people is clearly an important issue for maintaining good health. Unfortunately, there were no independent assessments of the housing quality in this study, as it was not financially feasible to undertake such assessments. Consequently, the study relied on the self-reported data. On that basis, problems reported may have been influenced by the respondents’ subjective view point. There is some evidence to suggest that households in poorer circumstances have a more negative world view and are more likely to report moderate to severe illhealth (Marsh et al., 1999). Negative affect may also increase the likelihood of reporting more difficulties with housing. However, a recent longitudinal study found that an initial assessment of a poor quality internal
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home environment was sufficient to predict the onset of depression in a one year follow up assessment of older people without depressive symptoms at baseline (Stewart et al., 2002). Such findings provide a strong case for the negative impact of housing problems on older people’s mental health. Moreover, a subjective assessment allows older people to voice concerns about their homes that may be missed by an objective assessment (Golant, 1984). This may be particularly important in relation to the physical functioning of the occupant, and any difficulties experienced. Despite the lack of an objective assessment of the housing, there is some independent evidence to suggest that some of the housing in this sample may have been of poor quality. The Welsh Index of Multiple Deprivation (National Assembly for Wales, 2000) reports a rank score in housing deprivation2 for the 866 electoral wards in Wales, with a score of 1 being the most deprived and 866 being the least deprived. In relation to the study sample five of the six sites were in the worst hundred in Wales, with one of the areas being ranked the worst. The sixth area was ranked 230. As this study used random sampling procedures it is likely that some of the worst housing in Wales was included in this study. This provides some further support for our results demonstrating the negative impact of housing on health. Whilst this analysis sought to investigate older peoples’ health status and housing circumstances, it did not attempt to address why older people may disproportionately occupy inappropriate housing. This has important implications when considering how such problems might be rectified. It has been suggested that poor housing conditions are often experienced by older people due to declining incomes on entry to retirement and the subsequent impact on the ability to afford repair work (Leather et al., 1994). Considering this suggestion in the Welsh context, Wales has one of the lowest gross domestic product (GDP) figures and the lowest disposable income per head compared with other UK regions. GDP per head is approximately 80% of the European Union average (Welsh Office Statistical Directorate, 1998). The Welsh House Condition Survey reported that the median gross annual income for single pensioner households was the lowest for all groups in Wales at £4,500, under half of the median gross annual income for all households (£9,400). In addition, 43% of single pensioner households reported a gross household income of less than £4000 (The National Assembly for Wales, 2001). There are some estimates as to what is an acceptable income for someone of retirement age. One suggestion is that a ‘modest but adequate’ income for a 2 The indicators used to assess housing deprivation are the proportion of properties in disrepair, the proportion without central heating and the proportion that lack roof or loft insulation.
single pensioner would be between £130 and £142 (Family Budget Unit, 1997). However, Age Concern recommended that pensioners should be entitled to a ‘social wage’ of £150 per week (Midwinter, 1998). The NatWest Pensions Index proposed that an income of £193 per week was required for a ‘financially comfortable retirement’ (NatWest, 1999). Within this study although there was a large amount of missing responses to the income question, of those who did answer over half (56%) had an income of less than £140 per week, generally reflecting the Welsh context. The combinations of poor housing stock and low levels of income in Wales have implications for the targeting of grants and other funding schemes. The results of this study imply that assistance should be available to all older people who may be experiencing housing problems that could impact on their health status. However, financial resources no longer meet population needs (Groves et al., 1999) and assistance is often means tested. Quality and Choice (Department of Environment, Transport and the Regions, 2000) states that grants should be prioritised for households at most risk who cannot afford to repair their homes. However financial aid varies, depending on property ownership. At the time of writing, some major changes are underway in the availability of grants for private tenants and owner occupiers. Although Disabled Facilities Grants will remain, the power of local authorities to provide help for repairs in this sector is now optional. In order to meet future need, partnerships and collaboration between housing, health, social services and the voluntary sector that facilitate the pooling of budgets may be the way forward. Although it has been suggested that collaboration between housing, health and social care agencies is difficult to achieve (Arblaster et al., 1996), there are a number of innovative partnerships that have succeeded in such initiatives (see Windle and Burholt, 2001). Home Improvement Agencies such as Care and Repair, who provide valuable advice and practical assistance to help older householders repair and maintain their homes are now beginning to benefit from financial input from other sectors (Easterbrook, 2002). The development of home maintenance initiatives by local authorities may also assist some of the low income households that cannot afford to maintain or adapt their current homes (Groves et al.,1999). Housing interventions for older people are relatively low in cost compared to the costs of other ‘stay at home’ packages (Smart and Means, 2000). There is also good evidence from intervention studies demonstrating how improving housing can improve health and mental health (Thompson et al., 2002). Adaptations that increase competence within the house can positively contribute to the well-being and behavioural activity of the older person and are hugely effective in restoring lost independence (Heywood, 2001). In recent research
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regarding adaptations in a Welsh Unitary Authority, Heywood (2001) found that older people referred to items such as stair-lifts and walk-in showers as ‘a godsend’ and ‘wonderful’. After the installation of a shower one woman noted that she no longer needed help to bathe and this was ‘the difference between existing and living’. She felt that the adaptations by restoring her independence had restored her life. Housing modifications can also reduce the risk of accidents. Simple changes to the home, such as handrails can reduce the risk of falling (Heywood, 2001). Such ‘lower level’ repairs and adaptations are often particularly suited to the needs of older people. In conclusion, this study has tentatively demonstrated how housing difficulties can impact on the health status of older people, and highlighted some important differences in health in a geographical context. The study used random sampling procedures, which endeavoured to be representative of the population, and achieved a sample size which was more than sufficient for statistical power. Consequently we feel that the findings should be given consideration. To address the housing difficulties and subsequent health inequalities, the ability to access financial resources for repairs and adaptations will require considerable financial outlay. Given the general poor financial situation of older people found in this study and in Wales in general, an increase in the level of income of pensioners in Wales may subsequently assist older people to remain independent in their own homes and ‘age in place’.
Acknowledgements The study represents collaborative research that has arisen from Gwynedd Rural Ageing Network (GRAN). GRAN is a wide network involving those with concerns in the area of services to older people in Gwynedd, North Wales. This work was funded by Wales Office for the Research and Development of Health and Social Care (WORD).
References Acute Services Development Group, 2000. Access and Excellence, Acute Services in Wales. The National Assembly for Wales, Cardiff. Age Concern, 2001. Hypothermia and excess winter deaths. Age Concern Policy Papers Ref. 0401. Age Concern, London. Arblaster, L., Conway, J., Foreman, A., Hawton, M., 1996. Interagency working for housing, health and social care needs of people in general needs housing. Joseph Rowntree Foundation Findings, Housing Research 183. Baltes, M.M., Wahl, H-W., Schmid-Furstoss, U., 1990. The daily life of the elderly at home: activity patterns, personal
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Health & Place 12 (2006) 267–278 www.elsevier.com/locate/healthplace
Housing related difficulties, housing tenure and variations in health status: evidence from older people in Wales Gillian S. Windlea,, Vanessa Burholta, Rhiannon T. Edwardsb a
The Centre for Social Policy Research and Development, The Institute of Medical and Social Care Research, University of Wales, Bangor, Ardudwy, Holyhead Road, Bangor, Gwynedd, Wales LL57 1PX, UK b The Centre for the Economics of Health, The Institute of Medical and Social Care Research, University of Wales, Bangor, UK Accepted 1 August 2004
Abstract This study aimed to examine housing-related difficulties, the relationship with housing tenure and the subsequent influences on health status in a population sample of older people in Wales. Comparisons with health status normative data were undertaken to determine any geographical differences. A random sample of respondents were interviewed in their own homes (N ¼ 423). Data included demographic information, self-reported health status, housing problems, tenure and factors relating to energy efficiency. Univariate analysis found that owner occupiers reported the least housing difficulties and the best health status. Those in public rented properties experienced the most difficulties and the poorest health. The health status of the sample was generally poorer than the norms. Multivariate analysis found that housing difficulties, being cold with current heating and hours spent at home predicted poorer health status. This suggests that characteristics of the home environment may help to explain the differences between tenure and health. Considerable financial outlay may be required to meet policy initiatives that support older people remaining independent, autonomous and able to ‘age in place’. r 2005 Elsevier Ltd. All rights reserved. Keywords: Older people; Independence; Housing conditions; Self-reported health; Housing tenure; Wales
Introduction Housing has been described as the foundation of social care (National Housing Federation, 1999; Harrison and Heywood, 2000) and is highlighted in the Framework for a National Housing Strategy for Wales as being an important factor in the successful delivery of ‘community care’ especially for older people wishing to remain in their own homes (National Consultative Forum on Housing in Wales, 1999). The importance Corresponding author. Tel.: +44 1248 383968; fax: +44 1248 382229. E-mail address: [email protected] (G.S. Windle).
of housing is further reinforced in the United Nation’s International Plan of Action on Ageing (2000) which states ‘suitable housing is even more important for the elderly, whose abodes are the centre of virtually all of their activities’. This paper reports some of the findings from a study entitled Housing for an Ageing Population: Planning Implications (HAPPI). HAPPI was designed to provide evidence on housing needs and preferences to inform policy decisions and address many of the requirements of the National Assembly for Wales. The objectives here were to examine housing difficulties, their relationship
1353-8292/$ - see front matter r 2005 Elsevier Ltd. All rights reserved. doi:10.1016/j.healthplace.2004.08.010
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Table 1 The links between housing and health Author and date
Housing problem
Health problem
Strachan and Elton, 1986 McCarthy et al., 1985 Packer et al., 1994
Damp and mould Poor ventilation
Asthma and Respiratory illness
Collins et al, 1985 Collins, 1986, 1987 Age Concern, 2001
Cold temperatures & Lack of efficient heating
Respiratory illness Rise in blood pressure Hypothermia
Birtchnell et al., 1988 Hopton and Hunt, 1996
General poor quality
Depression Depression and anxiety
Macintyre et al, 1998 Ellaway and Macintyre, 1998
with housing tenure and the influences on the health status of a population sample of older people in Wales. It has been estimated that older people spend between 70% and 90% of their time in their home (Baltes et al., 1990, Czaja, 1988, Gabb et al., 1991), therefore, an appropriate living environment should be considered crucial to maintain and/or enhance independent living (The Royal Commission on Long Term Care, 1999). Retaining independence and autonomy are recognised as being crucial for maintaining quality of life, underpinning policy and practice (UN/Division for Social Policy and Development, 2000, Welsh Assembly Government, 2003). There is considerable evidence suggesting that poor quality housing can have an adverse effect on the health of its occupants (see Table 1), recently confirmed in a systematic review of the literature (Thompson et al., 2002). For older people, health is widely acknowledged as one of the key elements of the ageing process (e.g. Siddell, 1995, Wenger et al., 2001). Findings from a longitudinal study show that the most salient life domain for older people is reported to be health and the maintenance of mobility (Wenger et al., 2001). Yet health and mobility difficulties can be exacerbated by an inappropriate home environment, affecting the ability to manage at home, which subsequently can impact on independent living (The Royal Commission on Long Term Care, 1999; The Office for National Statistics, 1999), and well-being (Lawton, 1989). Accidents, in particular falls are among the commonest causes of death and disability in older people (Effective Health Care, 1996). In total, 40% of fatal accidents occur in the home and 85% of these involve people over the age of 65 (Effective Health Care, 1996). The ability to heat the home is imperative, as the older population are far more susceptible to the
Limiting longstanding Illness
effects of cold temperatures (Environmental Epidemiology Unit, 1999). A number of UK studies have found that houses occupied by older people are slightly colder than average (Collins, 1993) and the Welsh House Condition Survey (National Assembly for Wales, 2001a) found that older people were less likely to live in a home with central heating. The absence of central heating is considered to be an indicator of housing deprivation (National Assembly for Wales, 2000). It could be argued that difficulties experienced at home by some older people are related to their functional status, and not necessarily a reflection of the condition of the property. On the other hand, if functional limitations are exacerbated by inappropriate housing conditions, then some occupants could face an increased risk of a poor health outcome. Previous research has identified that Wales has a relatively high level of ill health, and the health of the Welsh population as measured by life-expectancy and long term limiting illness is worse than the UK average (Acute Services Development Group, 2000). It is not being suggested here that these high levels of ill health are purely a consequence of poor housing however there are a number of factors relating to housing in Wales that are indicative of potential health risks. Poor and unfit housing is often associated with the age of the property, with older properties more likely to be classed as unfit (Leather et al., 1994; National Assembly for Wales, 2001a). The Welsh housing stock is older and in worse condition than in England: 8.5% of the housing stock was rated as unfit for habitation in 1999, which is above the level in England (National Consultative Forum on Housing in Wales, 1999). The 1998 Welsh House Condition Survey found that 14.9% of dwellings built before 1919 were unfit for habitation compared to 2.4% built after 1964. In Gwynedd (the study area), 48% of the housing stock was constructed before 1919 of which
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17% was class as unfit1 (National Assembly for Wales, 2001a). Housing quality varies further when examined by tenure. The highest proportions of unfit houses are in the private rented sector (Department of the Environment and Transport and the Regions, 2000). In Wales, research has demonstrated that 11.9% of owner occupied houses; 25.5% of private rented houses; 15.8% of LA rented houses and 6% of housing association rented houses were considered unfit. With the exception of the housing association houses these levels were consistently higher that the proportions of unfit housing in England (5.5% owner occupied; 20.5% private rented; 6.9% of LA rented and 6.7% of housing association) (Leather and Morrison, 1997). Housing tenure is also associated with the age of occupants. The majority of older people are owneroccupiers (Office for National Statistics, 1999). Analysis of the General Household Survey demonstrated that in the age group 65–74, 66% were owner occupiers and owned their properties outright in comparison with 19% of the 45–54 age group. Wales has the largest proportion of home ownership in the UK (72%) and older home owners are more likely than other households to live in properties built before 1919 and least likely to live in properties built after 1965 (Hancock et al., 1999), potentially increasing the likelihood of their homes being of poorer quality. Poor quality housing in the UK has been found to be disproportionately occupied by single older people (Leather and Morrison, 1997). These properties tended to be older and in the private rented sector (Leather and Morrison, 1997). The Welsh House Condition Survey also found that the highest proportion of unfit properties in the owner occupied sector (12.2%) and in the private rented sector (25.7%) belonged to single people of a pensionable age. Older people in Wales may then have an increased chance of health risks from their properties, which may vary by tenure. Variations in health status and mortality have been linked with housing tenure (owner occupied, or rented property). Home ownership is often found to be an independent predictor of better general health status (Thompson et al., 2002). Conversely, it has been found that living in rented property is associated with low health-related quality of life and low self-reported health status (Kind et al., 1999). A longitudinal study has found that living in rented property is associated with higher death rates compared to home-ownership. 1
The fitness standard (Housing Act 1989) states that a dwelling should meet a number of requirements, e.g.: be free from disrepair and damp, have adequate provision for lighting, have, for exclusive use of the occupants a bath or shower and a wash basin with hot and cold water, have adequate facilities for food preparation and adequate provision for heating and ventilation.
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Mortality was 26% higher for male and 21% higher for females renting local authority properties than owners during 1971–1981. In the following period (1981–1989) the excess mortality among those renting was 22% for males and 32% for females (Filakti and Fox, 1995). In Scotland a population sample survey found that living in council rented accommodation, compared to living in private rented accommodation or being an owner-occupier, has been independently associated with ratings of both significant and severe chronic pain that had persisted for at least 3 months (Smith et al., 2001). The reasons why housing tenure might determine variations in health status have until recently been given little attention (Ellaway and Macintyre, 1998). One suggestion is that the variation in health status for housing tenure reflects the socio-economic status of its occupants. Home-ownership is often regarded as an indicator of financial wealth, and socio-economic status is strongly related to health status (Harding et al., 1997). The notion that housing tenure predicts health status as it represents socio-economic status was examined by Macintyre et al. (1998). Using data from two adult cohorts in Scotland these authors found that home ownership was a predictor of better health even when factors such as income were controlled for. They concluded that health may vary perhaps because there were health promoting or health damaging factors in the properties across different housing tenures, these being the least problematic in owned properties. Building on this finding Ellaway and Macintyre (1998) hypothesised that aspects of tenure (housing conditions and quality of the surrounding environment) could be associated with health, independent of income or social class. A survey of 318 40 year olds and 373 60 year olds in Scotland provided data on tenure and a number of potential housing stressors, such as damp or condensation, cold properties and noise. Their analysis suggests that poor housing and poor quality local environment contributed to poor health, independent of income. Thus, the quality of the housing stock across tenure groups may expose people to a home environment that can have a detrimental effect on their health. Considering that house conditions can impact on health outcomes, appropriate housing for older people is clearly important. Within Wales there is more poor quality housing than the rest of the UK and the quality of the housing stock varies across housing tenure. Given the increased likelihood that as proportionally more older people live in poor quality housing they may experience housing-related difficulties, this paper aimed to examine whether health variations across housing tenure were due to housing-related difficulties. In line with the literature, it was hypothesised that:
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1. Respondents in private rented accommodation would experience the most problems, whilst owner occupiers would experience the least. 2. Owner occupiers would report the best health status, those in rented accommodation the poorest. As there are differences between Wales and the rest of the UK for health status and housing quality, the third hypothesis was that: 3. The study sample would have poorer health than UK population norms when examined across housing tenure. Finally a model was constructed to determine the independent influences of the variables on health status. In line with the literature it was hypothesised that: 4. Characteristics of the home environment may help to explain differences in health between tenure groups. Housing difficulties would independently predict poorer health, irrespective of tenure.
Method Sampling The sample for HAPPI was selected from the county of Gwynedd in North Wales to provide a representative sample from a diverse range of areas. These were a dispersed farming community, a retirement destination, an ex-quarrying community, an urban area, a concentration of difficult to let sheltered housing, and a market town. In order to identify the appropriate age group and to achieve a random sample, a door-to-door census of occupied households in the chosen communities was conducted. Electoral rolls for the areas were obtained containing a total of 8098 names and addresses. Addresses were entered onto a census sheet for interviewers to record occupants’ details. Interviewers were instructed to also call at any unlisted properties in the areas to ensure that the final sample would be as representative as possible of the locality. Information was obtained on the occupants’ age, gender and preferred language of interview (English or Welsh). Potential respondents (aged 70 or over) were entered onto a database. Random sampling procedures were used to draw a proportional sample from each community. These were 8% for the dispersed farming community, 27% for the retirement destination, 12% for the exquarrying community, 8% for the urban area, 20% for the area with difficult to let sheltered housing, and 24% for the market town. The smaller sample from the urban area was due to the large proportion of students in this ward.
Interviewing Interviewers were trained by the research team. Guidelines for professional conduct and ethical considerations were circulated to the interviewers prior to the meeting and were reiterated at the training sessions. After training, interviewers understood the necessity of obtaining consent from interviewees, issues regarding confidentiality, contact with respondents and the confounding affect from the presence of other family members or friends during the interview session. English and Welsh versions of the questionnaire were used by the interviewers. The former North Wales Health Authority was responsible for front-back translation and calibration of items in order to represent the intent of the questionnaire items within the cultural context. Respondents selected for inclusion in the sample were sent a letter describing the study and indicating when an interviewer might call. Respondents were asked to contact the Principal Investigator if they did not wish to take part in the study. Interviewers called at the home of the respondents to obtain an interview, or to make appointments for a convenient date. Welsh speaking interviewers were matched with Welsh speaking respondents. Administering the questionnaire took place in the respondents own home in the form of a structured faceto-face interview. Interviewing took place between September 2001 and February 2002. The final sample size was 423, representing a response rate of 54% of those identified in the census and randomly selected for interview. A high proportion (19%) refused to be interviewed, 12% refused as they were too ill, 8% could not be contacted, and 7% refused for other reasons, such as they were not residents of the area (holiday property). The project target initially was 500. This number was decided on so as to be powerful enough to enable planned complex statistical modelling to be performed. However, responses dropped during the course of the data collection. Feedback from interviewers suggested that potential respondents were concerned about allowing interviewers into their homes, due to a brutal murder of a local older woman. Interviews were halted to avoid causing any unnecessary anxiety. The final sample was felt to be sufficient to undertake the analysis.
Measures General health Although the literature demonstrates a wide variety of health outcomes as a result of poor housing, for the purpose of this analysis a simple measure of self-assessed health was used. Such measures have been demonstrated to be strong predictors of mortality (Office for National Statistics, 1999).
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Respondents’ assessed their own health state on the self-rated Visual Analogue Scale (EQ-VAS) ranging from 0 (worst health state) to 100 (best state). This scale is part of the EuroQoL EQ-5D health state classification, and was included in the study for (a) its simplicity, (b) it enabled comparison with population norms and c) the purpose of some planned economic analysis. The authors of the EQ-5D state it is a reliable measure of health status and it is used across a wide range of settings (Brooks, 1996). It is advocated as an easy to use measure, making it a potentially popular choice for use with older people (Brooks, 1996). The scale was enlarged so as to be visible to respondents’ with poor eyesight. Respondents’ were asked to mark on the scale where they viewed their health state today. (Fig. 1).
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Population norms for the EQ-VAS derived from a sample of 3395 respondents are available for the UK (Kind et al., 1999). This normative data was obtained from a survey designed to collect data on health state valuations and self-reported health using the EuroQoL EQ-5D questionnaire. The sample was representative of the population with respect to gender, age and social class. Of the total sample 547 were aged 70 and over with a mean age of 76.5. Comparisons were drawn between the health status of the HAPPI sample and the population norms across the housing tenure categories. For the HAPPI sample the respondents’ ages were recoded into two groups, 70–74 and 75+ in order to match the normative data.
Your own health state today
To help people say how good or bad a health state is, we have drawn a scale (rather like a thermometer) on which the best state you can imagine is marked 100 and the worst state you can imagine is marked O.
Best imaginable health state 100
9 0
We would like you to indicate on this scale how good or bad your own health is today, in your opinion. Please do this by drawing a line from the box below to whichever point on the scale indicates how good or bad your health state is.
8 0
7 0
6 0
Your own health state today
5 0
4 0
3 0
2 0
1 0
0
Worst imaginable health state Fig. 1. EQ-5D Visual Analogue Scale (EQ-VAS).
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Housing It was not financially possible to undertake full structural surveys of the respondents’ properties, however respondents were asked questions relating to problems experienced with aspects of their homes. These related to aspects of the home environment that might enhance, maintain or have a negative impact on health status. Questions relating to difficulties that could be exacerbated by reduced physical functioning, such as difficulties with steps and stairs were also examined. Two questions were asked regarding warmth in their homes that were coded dichotomously (no/yes). ‘‘On the whole, during cold spells, are you warm in your home with the heating you use, without wearing extra clothing?’’ ‘‘During cold spells, are you warm in bed without wearing extra clothing or using an electric blanket?’’ Respondents were asked whether they had difficulties with items such as steps/stairs, heating, damp/condensation, draughts and difficulties using a bath/shower (see Table 3 for items). The answers were coded dichotomously (yes/no). For the purpose of multivariate analysis all of the ‘difficulty’ questions were collapsed together to give a continuous scale. Higher scores indicate poorer condition and more difficulties (range between 0 and 14). The reliability of the scale (Cronbach’s Alpha) was 0.62. There is some debate as to the acceptable level for good internal consistency, ranging 40.50 (Cronbach, 1951) to 0.70 (Nunally, 1978). In this instance 0.62 was felt to be sufficiently acceptable for analysis. The age that the property was built was recorded and whether the respondents had roof or loft insulation and central heating. The latter two items were included as they are used as indicators of poor housing in the Welsh Index of Multiple Deprivation (National Assembly for Wales, 2000). Respondents also provided information on the average amount of time they spent in their homes per day (24 h) and how long they had lived in their properties. Respondents indicated the tenure of their homes (owner-occupier, owned by child or other relative, rented from the local authority, rented from a housing association or privately rented). The normative data for housing tenure is categorised as owner/mortgage, private rented, public rented and other. The HAPPI questionnaire gained more detail on housing tenure than the EQ normative data categories. To make the comparisons with the norms the HAPPI data for owner occupier and child or other relative were combined to reflect the category owner/mortgage in the EQ norms. The categories ‘local authority rented’ and ‘housing association rented’ were combined to reflect the category
public rented in the EQ norms. Private rented remained the same. The category ‘other’ was excluded as the HAPPI sample contained data for only one respondent, and for four respondents in the normative data, which are not sufficient for parametric analysis. General demographic data (age, gender, marital status and income) were also obtained.
Analysis The relationship between the individual housing difficulties and tenure were examined by cross-tabulations to determine the proportions experiencing difficulties in each tenure group, and the Spearman Chi Square test to determine if any differences between tenures are significant. Independent sample t-tests were used to determine differences in health status between the HAPPI sample and the population norms across the housing categories, as this is the recommended procedure in the population norms handbook (Kind et al., 1999). The unequal sample sizes across the tenure groups suggested that the equality of variance assumption for parametric analysis may be violated. To determine differences in self-reported health and housing difficulties between the tenure categories, one way ANOVA’s were run first and the Levene test for equality of variance computed. This was not significant for selfreported health, but significant for housing difficulties. A Kruskal–Wallis test was used for the housing difficulties analysis. To determine the independent influences of the variables on health, a hierarchical multiple regression model was developed with selfreported health status as the dependent variable.
Results Four respondents were excluded from this analysis as their scores on the EQ-VAS were difficult to interpret, and five refused to answer, leaving a final sample of 411 for the analysis. The age of the respondents’ ranged from 70 to 99, with the mean age being 78 (standard deviation ¼ 5.55). Fifty nine per cent were female and 41% male. 52% were married, 7% single, 37% widowed and 4% were divorced. 41% lived alone. The mean selfreported health score of the whole sample was 70.40 (standard deviation ¼ 18.71). In total, 79% (n ¼ 333) of the respondents fell into the owner/mortgage category, 18% (n ¼ 72) lived in public rented properties and 3% (13) in private rented properties. In total, 40% of the respondents lived in housing built in or before 1919. The majority (85%) had lived in their houses for 6 or more years, and 33% of these had lived there for 30 or more years. Few respondents lacked essential amenities such
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as hot water (n ¼ 3), an inside flush toilet (n ¼ 4), or cooking facilities (n ¼ 4). Respondents in this study spent an average of 19.97 h (s.d. 4.1) in their homes. This is equivalent to an average of 83% of the day spent at home. Nineteen per cent reported that during cold spells they were not warm in their homes without having to wear extra clothing. Of these, 65% were owners, 28% public renters and 6% private renters. Twenty four per cent reported that during cold spells they were not warm in bed without wearing extra clothing or using an electric blanket. Of these 72% were owners, 23% public and 5% private renters. Just over a third of the respondents (38%) had no central heating and 17% had no roof or loft insulation. Of those who reported their weekly income, 56% had £140 per week or less (see Table 2). Table 3 shows the proportion of the respondents that reported difficulties with their housing. Those in rented accommodation tended to report more problems than those who owned their homes, although there were some differences between the types of rented tenure. When the individual items were collapsed together, there was a significant difference in the number of housing problems between the tenure groups (H ¼ 9.82, 2, po0.01). Owner occupiers had the lowest average scores (m ¼ 0.94/mean rank ¼ 199.49) indicating the fewest difficulties followed by those in private rented properties (m ¼ 1.64/mean rank ¼ 231.71) whilst those
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Table 3 Proportions reporting difficulties Problems with
Steps/stairs Floor covering Heating*** Damp/ condensation** Draughts*** Lighting*** Noise* Decoration* Repairs Lack of facilities** Size of dwelling Difficulty using bath/shower Difficulty using WC Security** Outside access
Owneroccupier
Tenure Public rented
Private rented
17.0 1.0 5.0 7.0
17.0 1.0 17.0 19.0
0.0 0.0 14.0 22.0
7.0 1.0 5.0 8.0 15.0 1.0 5.4 11.0
26.0 1.0 13.0 16.0 20.0 0.0 7.1 16.0
14.0 14.0 7.0 21.0 22.0 14.0 0.0 14.0
2.0 1.0 7.0
4.0 10.0 4.0
7.0 7.0 7.0
*po0.05. **po0.01. ***Po0.001.
in public rented had the highest average scores (m ¼ 1.71/mean rank ¼ 243.51). Table 2 Income
Tenure and health
Weekly income (£ sterling)
Frequency
Percentage
0–69.99 70–79.99 80–89.99 90–99.99 100–119.99 120–139.99 140–159.99 160–179.99 180–199.99 200–219.99 220–239.99 240–259.99 260–279.99 280–299.99 300–319.99 340–359.99 360–379.99 380–399.99 400+ Total Missing Total
19 35 15 27 45 21 26 20 16 11 6 9 7 8 6 2 1 2 13 289 130 419
6.6 12.1 5.2 9.3 15.6 7.3 9.0 6.9 5.5 3.8 2.1 3.1 2.4 2.8 2.1 0.7 0.3 0.7 4.5
There was a significant difference in the self-reported health status of respondents’ by housing tenure (F ¼ 4.90, 407, po0.01). Owners reported the best health score (m ¼ 71.81), followed by those in private rented (m ¼ 66.15) whilst those in public rented reported the worst score (m ¼ 64.39). Post hoc analysis (Tukeys HSD) found the largest difference (m ¼ 7.42) was between owner occupiers and respondents in public rented accommodation. Comparison with population normative data Fig. 2 presents the mean self-reported health score for respondents aged 70–74 years (n ¼ 134) compared to the UK population norms (n ¼ 219). In comparison to the population norms, our sample of owner occupiers and those living in private rented accommodation had lower self-reported health scores. An independent sample t-test found the difference between the self-reported health status of the owner occupiers in the HAPPI sample to be significantly less
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90 HAPPI NORMS
85 78.7
Mean score
80 75
Predictors
75
1
67.6
65 60 55 50 Owner
Private rented
Public rented
Fig. 2. Self-reported health: 70–74 age group.
90 HAPPI NORMS
85 78.58
Mean score
80
Self-reported health status
72.2 71.8
71.2
70
75
Table 4 Regression of housing variables on health status. Standardised coefficients of included variables
72.5
71.82
3
b
b
0.29 0.07 0.06
0.01 0.06 0.03
0.16* 0.06 0.04 0.003
0.05
0.22*** 0.02 0.17* 0.08 0.77 0.14* 0.15
*po0.05 ***po0.001.
67.58
70
b Control variables Gender 0.03 Age 0.09 Income 0.09 Housing tenure Public rented Private rented Housing problems Difficulties scale Cold in bed Cold with current heating Pre-1919 No roof/loft insulation Average number of hours at home 0.02 Changes in r2
2
64.5
65
61.42
60
Multiple regression model
55 50 Owner
Private rented
Public rented
Fig. 3. Self-reported health: 75+ age group.
than the population norms (t ¼ 4:76; df ¼ 239; po0.01). Owing to the low frequency for the category private rented (n ¼ 7) no statistical tests were performed. For respondents in public rented properties there were no significant differences in the self-reported health status between HAPPI the sample and the population norm. Fig. 3 shows the corresponding self-reported health status by housing tenure for respondents aged 75 years and over in the HAPPI sample (n ¼ 275) and the normative data (n ¼ 302). The figure shows that both the HAPPI sample and population norms follow the expected pattern, with owner occupiers reporting better health than those in either private or public rented housing. For each housing category, the self-reported health status of the respondents in the HAPPI sample is lower than national norms. This difference was statistically significant for owner occupiers (t ¼ 3:94; df ¼ 362; po0.01) and those living in public rented accommodation (t ¼ 2:03; df ¼ 181; po0.05). No statistical test was undertaken for those respondents living in the private rented sector due to the small sample size for this group (n ¼ 6).
Predictor variables were entered into the model in blocks. The improvement in the explanatory power of the model was assessed for each block of variables. The first block consisted of demographic factors (age, gender, income). The second block of variables included the three housing tenure categories (owner, private rented and public rented). The third block contained the housing-related problems (housing difficulties scale, whether or not property was built in or before 1919, whether during cold spells respondents are warm at home with the heating used without wearing extra clothing, whether or not during cold spells respondents were warm in bed without wearing extra clothing or using an electric blanket, the average number of hours spent at home each day and whether or not respondents had roof or loft insulation and central heating). Table 4 summarises the results of the stepwise regressions. The coefficients for the variables excluded during the running of the analysis are not reported. Without including the housing problems living in public rented accommodation predicts poorer selfreported health. When the housing problems are included, controlling for age, gender and income, housing tenure is no longer significant whilst more housing-related difficulties, feeling cold at home with current heating and more hours spent in the home predicted poorer health status.
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Discussion The aim of this study was to examine housing difficulties, their relationship with housing tenure and the influences on the health status of a population sample of older people in Wales. The first hypothesis was partially supported. Owner occupiers experienced the least problems, which was predicted from the literature. Respondents in private rented accommodation had more difficulties than owner occupiers, but it was respondents in public rented accommodation who had the highest number of difficulties. This finding may be partially explained considering that within Wales there is a substantial backlog of at least £750 million of improvements and repairs that are needed in this sector (National Assembly for Wales, 2001b), suggesting that the housing quality in this tenure group is particularly poor. The second hypothesis was supported: owner occupiers reported the best health status. In addition, respondents in public rented and private rented housing both reported health scores below the sample mean, whilst owner occupiers were higher than the sample mean. This finding supports other research where owner occupiers have better health (Thompson et al., 2002), and renters have poorer health (Kind et al.,1999; Smith et al., 2001). There were also differences between the health status of our sample and the UK population norms. These findings suggest that the health status of the HAPPI older population sample, particularly the oldest cohort (75+), is worse than the UK population norms when examined by housing tenure. It is difficult to infer that the poorer health status within this sample of older people, in comparison to the normative data, was purely a consequence of housing. A clear factor limiting any generalisability of these results was the design. Crosssectional designs, such as that employed in this study, can be confounded by the effects of past health behaviours (Carr-Hill, 2000; Marsh et al., 1999). A longer time period to study the effects of poor housing would determine the effects on health more accurately (Barrow and Bachan, 1997). Also, this is a post hoc analysis undertaken on data obtained from a larger study. Consequently, the sample sizes within the tenure groups are unequal, and are quite small for those in private rented accommodation. Despite the limitations of the design the research literature provided some underlying evidence for the differences found in this study in the context of our hypotheses. Specifically, within Wales there is more poor quality housing across all tenure groups than the rest of the UK, which is disproportionately occupied by older people. Likewise the health of the Welsh population as measured by lifeexpectancy and long-term limiting illness is worse than the UK average (Acute Services Development Group,
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2000). Although the literature provided some explanation, the link found between tenure and health was fairly descriptive, and required some further exploration. It was the purpose of the final hypothesis (that health variations across housing tenure reflect housing-related difficulties), to provide some evidence for a possible mechanism to assist in explaining the differences. The first step of the regression model demonstrated that living in public rented accommodation predicted lower health status. However, when the housing variables were entered, it was respondents who experienced the most problems, who were cold in their home with their current heating and spent the most time in their home that had the lowest self-reported health status, irrespective of housing tenure. This suggests that the initial finding for variations in health status by housing tenure may actually reflect difficulties experienced in the properties in these tenure groups. That is, the home environment may be influencing health. The results of the analyses are generally in line with those of Ellaway and Macintyre (1998) who also found that housing tenure affected health because aspects of the home environment had an adverse affect on health. It should be noted that the significant prediction of poor health by spending long periods in the home could also be due to becoming housebound through poor health. However, this in itself could further increase the risk to health if the person was experiencing difficulties with their properties. Of particular concern is proportion (19%) of the sample that stated they were cold in their homes with their current heating without having to wear extra clothing. The average time spent at home each day was also high for the respondents and 38% of this sample had no central heating, potentially increasing their risk of hypothermia. Each year in Britain at least 30,000 people aged over 65 die as a consequence of winter conditions (Help The Aged, 1994). One study found that excess winter deaths-related to dwellings with low energy efficiency ratings and low indoor temperatures (Wilkinson et al., 2001). Attending to the heating conditions in the homes of older people is clearly an important issue for maintaining good health. Unfortunately, there were no independent assessments of the housing quality in this study, as it was not financially feasible to undertake such assessments. Consequently, the study relied on the self-reported data. On that basis, problems reported may have been influenced by the respondents’ subjective view point. There is some evidence to suggest that households in poorer circumstances have a more negative world view and are more likely to report moderate to severe illhealth (Marsh et al., 1999). Negative affect may also increase the likelihood of reporting more difficulties with housing. However, a recent longitudinal study found that an initial assessment of a poor quality internal
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home environment was sufficient to predict the onset of depression in a one year follow up assessment of older people without depressive symptoms at baseline (Stewart et al., 2002). Such findings provide a strong case for the negative impact of housing problems on older people’s mental health. Moreover, a subjective assessment allows older people to voice concerns about their homes that may be missed by an objective assessment (Golant, 1984). This may be particularly important in relation to the physical functioning of the occupant, and any difficulties experienced. Despite the lack of an objective assessment of the housing, there is some independent evidence to suggest that some of the housing in this sample may have been of poor quality. The Welsh Index of Multiple Deprivation (National Assembly for Wales, 2000) reports a rank score in housing deprivation2 for the 866 electoral wards in Wales, with a score of 1 being the most deprived and 866 being the least deprived. In relation to the study sample five of the six sites were in the worst hundred in Wales, with one of the areas being ranked the worst. The sixth area was ranked 230. As this study used random sampling procedures it is likely that some of the worst housing in Wales was included in this study. This provides some further support for our results demonstrating the negative impact of housing on health. Whilst this analysis sought to investigate older peoples’ health status and housing circumstances, it did not attempt to address why older people may disproportionately occupy inappropriate housing. This has important implications when considering how such problems might be rectified. It has been suggested that poor housing conditions are often experienced by older people due to declining incomes on entry to retirement and the subsequent impact on the ability to afford repair work (Leather et al., 1994). Considering this suggestion in the Welsh context, Wales has one of the lowest gross domestic product (GDP) figures and the lowest disposable income per head compared with other UK regions. GDP per head is approximately 80% of the European Union average (Welsh Office Statistical Directorate, 1998). The Welsh House Condition Survey reported that the median gross annual income for single pensioner households was the lowest for all groups in Wales at £4,500, under half of the median gross annual income for all households (£9,400). In addition, 43% of single pensioner households reported a gross household income of less than £4000 (The National Assembly for Wales, 2001). There are some estimates as to what is an acceptable income for someone of retirement age. One suggestion is that a ‘modest but adequate’ income for a 2 The indicators used to assess housing deprivation are the proportion of properties in disrepair, the proportion without central heating and the proportion that lack roof or loft insulation.
single pensioner would be between £130 and £142 (Family Budget Unit, 1997). However, Age Concern recommended that pensioners should be entitled to a ‘social wage’ of £150 per week (Midwinter, 1998). The NatWest Pensions Index proposed that an income of £193 per week was required for a ‘financially comfortable retirement’ (NatWest, 1999). Within this study although there was a large amount of missing responses to the income question, of those who did answer over half (56%) had an income of less than £140 per week, generally reflecting the Welsh context. The combinations of poor housing stock and low levels of income in Wales have implications for the targeting of grants and other funding schemes. The results of this study imply that assistance should be available to all older people who may be experiencing housing problems that could impact on their health status. However, financial resources no longer meet population needs (Groves et al., 1999) and assistance is often means tested. Quality and Choice (Department of Environment, Transport and the Regions, 2000) states that grants should be prioritised for households at most risk who cannot afford to repair their homes. However financial aid varies, depending on property ownership. At the time of writing, some major changes are underway in the availability of grants for private tenants and owner occupiers. Although Disabled Facilities Grants will remain, the power of local authorities to provide help for repairs in this sector is now optional. In order to meet future need, partnerships and collaboration between housing, health, social services and the voluntary sector that facilitate the pooling of budgets may be the way forward. Although it has been suggested that collaboration between housing, health and social care agencies is difficult to achieve (Arblaster et al., 1996), there are a number of innovative partnerships that have succeeded in such initiatives (see Windle and Burholt, 2001). Home Improvement Agencies such as Care and Repair, who provide valuable advice and practical assistance to help older householders repair and maintain their homes are now beginning to benefit from financial input from other sectors (Easterbrook, 2002). The development of home maintenance initiatives by local authorities may also assist some of the low income households that cannot afford to maintain or adapt their current homes (Groves et al.,1999). Housing interventions for older people are relatively low in cost compared to the costs of other ‘stay at home’ packages (Smart and Means, 2000). There is also good evidence from intervention studies demonstrating how improving housing can improve health and mental health (Thompson et al., 2002). Adaptations that increase competence within the house can positively contribute to the well-being and behavioural activity of the older person and are hugely effective in restoring lost independence (Heywood, 2001). In recent research
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regarding adaptations in a Welsh Unitary Authority, Heywood (2001) found that older people referred to items such as stair-lifts and walk-in showers as ‘a godsend’ and ‘wonderful’. After the installation of a shower one woman noted that she no longer needed help to bathe and this was ‘the difference between existing and living’. She felt that the adaptations by restoring her independence had restored her life. Housing modifications can also reduce the risk of accidents. Simple changes to the home, such as handrails can reduce the risk of falling (Heywood, 2001). Such ‘lower level’ repairs and adaptations are often particularly suited to the needs of older people. In conclusion, this study has tentatively demonstrated how housing difficulties can impact on the health status of older people, and highlighted some important differences in health in a geographical context. The study used random sampling procedures, which endeavoured to be representative of the population, and achieved a sample size which was more than sufficient for statistical power. Consequently we feel that the findings should be given consideration. To address the housing difficulties and subsequent health inequalities, the ability to access financial resources for repairs and adaptations will require considerable financial outlay. Given the general poor financial situation of older people found in this study and in Wales in general, an increase in the level of income of pensioners in Wales may subsequently assist older people to remain independent in their own homes and ‘age in place’.
Acknowledgements The study represents collaborative research that has arisen from Gwynedd Rural Ageing Network (GRAN). GRAN is a wide network involving those with concerns in the area of services to older people in Gwynedd, North Wales. This work was funded by Wales Office for the Research and Development of Health and Social Care (WORD).
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