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International Journal of Architectural Research Phillippa Carnemolla, Catherine Bridge
Archnet-IJAR, Volume 10 - Issue 2 – July 2016 - (38-51) – Original Research Articles
Copyright © 2016 Archnet-IJAR, International Journal of Architectural Research
38
ACCESSIBLE HOUSING AND HEALTH-RELATED QUALITY OF LIFE:
MEASUREMENTS OF WELLBEING OUTCOMES FOLLOWING HOME
MODIFICATIONS
Phillippa Carnemolla
Faculty of Built Environment
University of New South Wales, Sydney, NSW, Australia
Catherine Bridge
Faculty of Built Environment
University of New South Wales, Sydney, NSW, Australia
**Corresponding Author’s email address: phillippa.carnemolla@unsw.edu.au
Abstract
The multi-dimensional relationship between housing and population health is now well
recognised internationally, across both developing and developed nations. This paper
examines a dimension within the housing and health relationship – accessibility – that to
date has been considered difficult to measure. This paper reports on the mixed method
results of larger mixed-method, exploratory study designed to measure the impact of home
modifications on Health-Related Quality of Life, supported by qualitative data of recipients’
experiences of home modifications. Data was gathered from 157 Australian HACC clients,
who had received home modifications. Measurements were taken for both before and after
home modifications and reveal that home modifications were associated with an average
40% increase in Health-Related Quality of Life levels. The qualitative results revealed that
participants positively associated home modifications across six effect themes: increased
safety and confidence, improved mobility at home, increased independence, supported care-
giving role, increased social participation, and ability to return home from hospital. This
exploratory research gives an insight into the potential for accessible architecture to impact
improvements in community health and wellbeing.
Keywords: Home modification; housing; accessibility; disability; aging population
INTRODUCTION
At the core of this research is the fact that housing is more than bricks and mortar; it provides not
only shelter, but also influences a range of social and health outcomes (Thomson et al, 2009).
This study offers an understanding of how investing in housing design through a program of
home modifications directly influences measurable health outcomes in the form of Health Related
Quality of Life. (HRQoL) in the houses of older people and those living with a disability. This
examination of home modifications and HRQoL enables a broader understanding of the links
between accessible housing, aging, and disability and ultimately contributes to a picture of the
dynamic relationship between the built environment and community health and wellbeing in the
context of the changing health of populations due to ageing and disability.
Also critical to this research is the fact that most existing Australian housing was designed
with an ‘average user’ (a healthy, young, adult male) in mind (Burns, 2004; Heylighen, 2008;
Imrie, 2003). In the case of Australia, this has resulted in an older housing stock of predominantly
inaccessible housing (Carnemolla and Bridge, 2012). This pattern of ageing populations,
increased levels of disability, and older housing stock is a situation that is replicated across both
developed and developing nations (Brodsky, 2003; Liebig, 2000).
International Journal of Architectural Research Phillippa Carnemolla, Catherine Bridge
Archnet-IJAR, Volume 10 - Issue 2 – July 2016 - (38-51) – Original Research Articles
Copyright © 2016 Archnet-IJAR, International Journal of Architectural Research
39
Motivations for this research
The housing and health relationship has received increasing interest in recent years with a
number of systematic reviews (Gibson et al, 2011; Thomson, Petticrew, and Morrison, 2001;
Thomson et al, 2009) and is now considered one of the major environmental, as well as social,
determinants of population health (Marmot et al, 2008). Globally, many studies have investigated
the health of populations and their housing conditions, with a body of evidence that strongly
associates between poor health and poor housing (Bonnefoy, 2007; Bridge et al, 2003a;
Thomson et al, 2013). The findings in this study respond directly to calls for intervention studies
aimed at assessing the health effects of building modifications (Braubach, 2011) and elaborating
on the pathways between housing and health (Gibson et al, 2011).
In housing and health reports, housing interventions vary broadly from focusing on living
conditions, such as thermal or air quality, to housing poverty, to levels of accessibility within the
home. There has been little research measuring and comparing levels of access in housing by
comparing the physical built environment. Indeed the social impact of inaccessible housing is
difficult to measure because the association between housing and health is complex and causal
relationships can be hidden or influenced by multiple factors (Jacobs et al, 2010). This, in part,
explains the lack of data or research studies exploring the relationship between access and
community health and wellbeing. Despite there being an extensive international body of evidence
identifying non-shelter outcomes of housing and the subsequent impacts on vulnerable
populations (such as older people and those living with a disability), there is less research
exploring how the architectural attributes themselves can play a role in impacting non-shelter
outcomes for people.
This paper draws on the quantitative results of a larger mixed methods research study,
whereby the home modification experiences of 157 participants are examined, sourced from a
group of Australian Home and Community Care (HACC) clients. HRQoL data for both before and
after home modifications was collected in a survey and was measured using the Assessment of
Quality of Life (AQoL). This was converted to pre- and post-utility and dimension scores enabling
comparison.
This exploratory research project was designed to measure how incremental
improvements to the accessibility of housing has a direct impact on health and wellbeing
outcomes. The study design is single arm and captures the ‘before’ and ‘after’ data in a single
survey. The quantitative results suggest the existence of a positive relationship between home
modifications and HRQoL.
What is a home modification?
Throughout this paper, the term ‘home modification’ is used to describe the structural changes
made to the home environment to help people to be more independent and safe in their own
home and reduce any risk of injury to their carers and care workers (Adams et al, 2014). These
modifications are often prescribed by an occupational therapist and relate specifically to a
person’s health, comfort, and ability to live independently at home. Research into home
modifications has steadily increased since 1990 (Carnemolla and Bridge, 2015) and is
interdisciplinary, spanning the fields of housing and health.
Accessibility as it relates to home modifications
This paper is concerned with accessibility as it relates to architecture and the built environment.
Accessibility in this context can be understood to be an approach to the design, construction, and
improvements of the built environment that consider how people, regardless of their age or ability,
experience the design in terms of mobility, usability, independence, and equity. The term
accessibility is often used to describe the built environment alongside nuanced terms such as
International Journal of Architectural Research Phillippa Carnemolla, Catherine Bridge
Archnet-IJAR, Volume 10 - Issue 2 – July 2016 - (38-51) – Original Research Articles
Copyright © 2016 Archnet-IJAR, International Journal of Architectural Research
40
inclusive, barrier-free, visitable, and universal design. Home modifications, as measured in this
study, are an architectural intervention designed to improve the accessibility of people’s houses.
Measuring wellbeing in the context of how we experience the built environment
In a recent systematic review on home modification evidence (Author citation, 2015), all the
included studies that actively reported on links between home modifications and wellbeing had
positive findings (Ahmad, Shakil-ur-Rehman, and Sibtain, 2013; Lin et al, 2007; Allen, 2005);
however, they all measured home modifications as part of a multi-factorial intervention. Overall,
there has been relatively little direct investigation into how home modifications influence Health-
Related Quality of Life and wellbeing of recipients This study responds to the need for research to
be conducted on home modifications as a single intervention, rather than as a component of a
multi-factorial intervention. This enables a unique understanding of the impact of the built
environment independent of other interventions.
Wellbeing is a broad concept that integrates physical, mental, and social domains. Global
indexes that attempt to measure the overall wellbeing of populations tend to have numerous
categories of wellbeing, illustrating how it is impacted by many life domains, e.g. the Organisation
for Economic Co-operation and Development (OECD) has developed a Better Life Index with 11
categories of wellbeing, housing being one, while the Canadian Index of Wellbeing has eight.
Housing encompasses a range of characteristics that are integral to wellbeing (Bratt, 2002).
Wellbeing has strong associations with the meaning of home and research suggests that, along
with other non-economic factors (such as health deterioration, family composition changes, and
local amenities), it is an important determinant in the housing choices of ageing populations
(Sabia, 2008).
This paper is specifically concerned with wellbeing as it relates to people’s experience of
changes made to the physical, built form of their housing following home modifications. This
study is designed to isolate and measure the influence of built form on the wellbeing of older
people and people living with disabilities and it uses an established measurement in the form of
Health-Related Quality of Life (HRQoL)
Measuring wellbeing as HRQoL
Health-Related Quality of Life (HRQoL) can be understood to be quality of life measurement in a
health care context. It is a multi-dimensional indicator that, like quality of life, incorporates
domains related to physical, mental, emotional and social functioning. These are also health-
related to the extent that they are influenced by disease, injury, treatment, or policy (Patrick and
Erickson, 1993). Measurements of HRQoL are converted to utility scores, a cardinal number, and
are often incorporated as a component in health economics (Sullivan, 2003). The measurement
of HRQoL changes associated with home modifications is an important indicator of the success
of such home modifications as a community health intervention, for a number of reasons.
• It is linked to self-care models of health care (Aalto, Uutela, and Aro, 1997; Buck et al,
2012) and autonomy (Vernooij-Dassen et al, 2005);
• It acknowledges person-centered (patient-centered in the case of health care
provision) models of health and care that are focussed not only on need but individual
choice and preference (Reeve et al, 2013); and
• It considers health in broader context than simply the body (e.g. wellbeing, social, and
environmental)
METHODS
The study is a single arm analysis of data on HRQoL gathered for both before and after home
modifications. Eligibility for the study was based on participants being community dwelling
recipients of Australian government supported care services (Home and Community Care
International Journal of Architectural Research Phillippa Carnemolla, Catherine Bridge
Archnet-IJAR, Volume 10 - Issue 2 – July 2016 - (38-51) – Original Research Articles
Copyright © 2016 Archnet-IJAR, International Journal of Architectural Research
41
clients). This meant that all participants would be either frail older people or people living with a
disability. All of the Home and Community Care (HACC) clients included in the study had
received home modifications prescribed by an occupational therapist. Participants were included
in the study where their home modifications had been completed within a six-month period prior
to the survey being distributed.
Data
Primary data was collected in a survey distributed to recent recipients of HACC-supported home
modifications via the two home modification service providers in New South Wales, Australia. The
survey was designed as a cross-sectional capture of longitudinal data (before and after), meaning
that self-reported data on care, HRQoL and related comments about experiences of home
modification were captured in a single survey at a single point in time, between one to six months
after home modifications were completed.
In addition to the survey data, data was available in the form of detailed health information
and home modification information. This was derived by matching the survey responses with the
relevant client files (which were de-identified on site) containing both medical diagnoses and
home modification information.
Measuring HRQoL in a survey
When measuring wellbeing or quality of life in relation to a particular intervention (such as home
modification), there are various kinds of surveys that can be used. The constitution of the World
Health Organization (WHO) defines health as “a state of complete physical, mental, and social
wellbeing not merely the absence of disease…” (WHOQOL Group, 1993). The more specific
concept of Health-Related Quality of Life (HRQoL) has evolved in recent decades to encompass
those aspects of overall quality of life that can be clearly shown to affect health, either physical or
mental. HRQoL instruments, also known as multi-attribute utility (MAU) instruments, measure the
utility of health states that is suitable for an economic evaluation such as a cost utility analysis.
Selection of the most appropriate instrument requires an understanding of a particular
instrument’s validity and reliability for the sample population being studied (Guyatt, Feeny, and
Patrick, 1993). The Assessment of Quality of Life was chosen for this research study because it
was based on Australian populations and in particular had been validated for older, community-
dwelling Australians.
The Assessment of Quality of life (AQoL)
The Assessment of Quality of Life (AQoL) instrument was developed by the Centre for Health
Economics, Monash University, Victoria, Australia. There are four versions of the AQoL, based
on length of instrument. AQoL-4D is the shortest, with 12 questions in a 1-2-minute completion
time. The AQoL-4D instrument was specially formatted to capture pre- and post- HRQoL data in
the single survey. Throughout the survey design process, the developers of AQoL-4D, Centre for
Health Economics, Monash University, were consulted about the modifications and the final
survey design was approved by representatives of the Centre for Health Economics. AQoL-4d
was the instrument chosen for this research.
The Assessment of Quality of Life (AQoL-4D) was integrated into the survey design to
determine Health-Related Quality of Life. AQoL-4D was administered in the form of 12 questions
to gather utility data regarding recipients’ experiences before and after home modifications. The
response was then converted to a utility score using SPSS statistic software. Australian
population norms are available for the AQoL (Hawthorne, Korn, and Richardson, 2013), which
has been validated for use in Australian health studies. The AQoL is also considered valid for
testing older, community-dwelling populations (Osborne et al, 2003). The resultant utility scores
are a measure of Health-Related Quality of Life.
International Journal of Architectural Research Phillippa Carnemolla, Catherine Bridge
Archnet-IJAR, Volume 10 - Issue 2 – July 2016 - (38-51) – Original Research Articles
Copyright © 2016 Archnet-IJAR, International Journal of Architectural Research
42
The aims of the survey were to collect a range of primary data unavailable in secondary data
sources including:
Demographic details about respondents, including age, income status, tenure, living status, and
health.
• AQoL-4D responses for before and after home modifications. This enables any
difference in utility scores (calculated from the AQoL-4D instrument) between before
and after home modification to be measured.
The survey design had to gather longitudinal data of HRQoL in a single capture. The successful
completion of the survey required a level of cognitive understanding that could differentiate
between before and after the home modifications. The single capture methodology is vulnerable
to recall bias on the part of respondents as they are being asked to provide data on two different
time points in the one survey. The survey was designed and laid out using Adobe Illustrator
software. The final format was a four-page, double-sided A4 document that was colour printed for
distribution. A total of 650 surveys were distributed with 157 valid responses received.
Table 1. Matrix documenting the quantitative variables analysed in the study.
Variable
Description
Unit
Measured
Source
AQoL Utility
Scores
AQoL utility
Utility (0-1)
Before and after
home
modifications
Self-reported in
survey and
converted
using SPSS
AQoL
Dimensional
Scores
Independent Living
Dimension
Cardinal score (0-1)
Before and after
home
modifications
Self-reported in
survey and
converted
using SPSS
Relationships Dimension
Cardinal score (0-1)
Before and after
home
modifications
Self-reported in
survey and
converted
using SPSS
Mental health Dimension
Cardinal score (0-1)
Before and after
home
modifications
Self-reported in
survey and
converted
using SPSS
Senses Dimension
Cardinal score (0-1)
Before and after
home
modifications
Self-reported in
survey and
converted
using SPSS
The AQoL-4D instrument estimates utility using a three-stage procedure. Items are (i) weighted
and combined using a multiplicative model to obtain dimension scores; (ii) these are weighted
and combined to obtain an initial AQoL score; (iii) this is then transformed econometrically to
produce the final estimate of a health state utility (Richardson, Peacock, Iezzi, Day and
Hawthorne, 2007). AQoL-4D utility algorithms for the conversion were downloaded from the
AQoL website.
Five variables were calculated in the data collection: an overall utility score and 4
dimension scores (uD) that related to the four sections within the AQoL-4D 12 questions. These
International Journal of Architectural Research Phillippa Carnemolla, Catherine Bridge
Archnet-IJAR, Volume 10 - Issue 2 – July 2016 - (38-51) – Original Research Articles
Copyright © 2016 Archnet-IJAR, International Journal of Architectural Research
43
five variables were collected in a pre- and post- format, for comparison between before and after
home modifications. The utility dimension (Ud) scores are not comparable with the total utility
score, but before and after Ud scores are comparable within each dimension. Dimensions
included independent living, relationships, mental health, and senses.
Inferential statistics
Statistical analysis was undertaken using the Statistical Package for Social Sciences (SPSS)
version 21. Descriptive statistical analysis was completed on the demographic information, AQoL
scores, and informal and formal care hour data. Primary collected data was confirmed as having
normal distribution and ANOVA testing was performed. The statistical procedures used in this
research included summary statistics, standard 𝝆 analysis. ANOVA testing is one-sided and
considered to be significant where 𝝆 value was < 0.05.
RESULTS
Sample Demographics
A total of 157 respondents were included in the analysis. This yielded a survey response rate of
24.1% (157 participants out of a sample of 650 eligible participants). A summary of the sample
characteristics follows:
• The average age of respondents in the sample was 72 years, with an age distribution
in line with HACC population data sets for NSW.
• In terms of being categorized as older people, or younger people living with a
disability, 13% (20) were younger than 55 years old and living with a disability and
87% (137) were frail or unwell older people.
• The gender balance approximated the NSW HACC population, with just over half
(54%) being women.
• Within the sample, 1.3% identified as Indigenous.
• The sample overall predominantly lived with a partner or spouse, followed by people
living alone. Those who lived alone were predominantly women while the men in the
sample tended to be living with a spouse or partner.
• The sample population tended to be financially supported by the aged pension.
• The sample featured overwhelmingly owner/ occupiers of their home.
Table 2. Demographic statistics of sample.
Count
Percentage
of total sample
GENDER
157
Female
85
54.1%
Male
72
45.9%
MEAN AGE (years)
71.86
HOUSING TENURE
Being purchased
2
1.27%
Fully owned
149
94.90%
Live with family members
2
1.27%
Own caravan and annex
and rent site
1
0.64%
Private rental
2
1.27%
Retirement village
1
0.64%
International Journal of Architectural Research Phillippa Carnemolla, Catherine Bridge
Archnet-IJAR, Volume 10 - Issue 2 – July 2016 - (38-51) – Original Research Articles
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Count
Percentage
of total sample
LIVING ARRANGEMENTS
Live alone
42
26.75%
Live with a spouse or
partner
84
53.50%
Live with family or friends
30
19.11%
SOURCE OF INCOME
Carers allowance
2
1.27%
Disability support pension
28
17.83%
Full aged pension
102
64.97%
Part aged pension
16
10.19%
Self-funded retiree
8
5.10%
Wage or salary full time
1
0.64%
INDIGENOUS STATUS
Indigenous
2
1.27%
Non-indigenous
155
98.73%
Health of the sample
Detailed health information was derived by matching the survey responses with the relevant client
files (which were de-identified on site), containing both medical diagnoses and home modification
information. This enabled a snapshot of the overall health diagnoses of the sample, indicating the
prevalence of co-morbidities. Co-morbidities (also referred to as multi-morbidities) are defined as
the ‘simultaneous occurrence of two or more chronic conditions’ (Taylor et al, 2010, 1).
More than half (53%) of the participants were diagnosed in their medical reports as frail
aged. Although on average, participants were diagnosed with two morbidities, a number of them
had up to five (5) chronic or life-threatening health conditions (Figure 9).
Figure 1. Analyses of diagnoses in the sample - average 2 diagnoses per participant.
International Journal of Architectural Research Phillippa Carnemolla, Catherine Bridge
Archnet-IJAR, Volume 10 - Issue 2 – July 2016 - (38-51) – Original Research Articles
Copyright © 2016 Archnet-IJAR, International Journal of Architectural Research
45
Figure 1 shows the frequency of all diagnoses reported in the data. A total of 323 morbidity
diagnoses were recorded for the 157 participants, with ‘frail aged’ being the most prevalent
diagnosis in the sample (54%), followed by arthritis (29%), neurological disorders (20%), and
cancer (19%).
Living situation and source of income
Twenty seven percent (27%) of the sample in this study reported living alone. The survey asked
respondents to nominate their main source of income. Analysis of the responses showed that,
overall, the full age pension was the predominant source of income (64%).
Housing tenure
Information on housing tenure was sought in the survey and revealed that the sample reported
overwhelmingly (95%) to be owner/ occupiers of their own homes.
AQOL data results
The AQoL data results (in the form of utility scores) reveal whether a home modification changes
the Health-Related Quality of Life of the recipient of a home modification. Analysis of the utility
scores and utility dimensions (independent living, relationships, senses, and mental health)
communicate the potential for home modification to impact autonomy and overall wellness/
wellbeing.
Inferential Statistics
Paired sample t-testing was conducted for all pre-post variables. All pairs were calculated to have
statistically significant results, except for the utility dimension of senses (uD3SEN), which
revealed a p score of 0.06. This result is unsurprising, given the two questions in the AQoL-4D
that relate to uD3SEN ask about vision and hearing changes, health aspects that in the dataset
were not targeted by home modifications specifically.
AQoL utility scores are reported in Figure 2 and display averages for:
• Average AQoL utility scores for the data set before and after home modifications
• AQoL utility scores for the Australian population of equivalent average age (70-
79) as reported by Hawthorne et al (2013)
• Australian population norm (includes all ages) as reported by Hawthorne et al
(2013)
The graphing of before and after average utility scores for the data set indicates that home
modifications resulted in an average increase of 0.12 utility points, increasing from 0.3 to 0.42 for
the study participants. However, the data set still has a lower average utility score than the
general Australian population (0.81) and the Australian population aged between 70-79 years
(0.76).
Figure 2. Analysis of the utility dimensions (uD).
International Journal of Architectural Research Phillippa Carnemolla, Catherine Bridge
Archnet-IJAR, Volume 10 - Issue 2 – July 2016 - (38-51) – Original Research Articles
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The AQoL-4D instrument used for this research included 12 questions about the following four
quality-of-life dimensions: Independent Living, Mental Health, Relationships, and the Senses.
Data from the survey was collated and analysed using AQoL algorithms in SPSS software. Mean
utility could also be analyzed according to the individual utility dimensions of AQoL-4D. Table 18
indicates how utility was distributed for each of the dimensions.
Table 3. AQoL Utility Dimension (uD) data.
AQoL Dimension
Mean Dimension
Score Before
Home
Modifications
Mean Dimension
Score After Home
Modifications
Change in
Dimension Score
% Change
from
Original
Score
uD Independent
Living
0.62
0.72
+0.10
+ 16%
uD Relationships
0.75
0.81
+0.06
+ 8%
uD Mental Health
0.82
0.87
+0.05
+ 6%
uD Senses
0.84
0.87
+0.03
+ 3.5%
Of note, and as anticipated, the biggest change in mean utility was in the Independent Living
dimension (+0.10). Levels of self-reported independent living, mental health, relationships, and
senses are all important influencers of utility scores in this context. As shown in Table 17, the
Senses dimension was the least significant of dimension variables and the difference in before
and after results is the smallest of all the dimensions. This was in line with expectation, due to the
Senses questions being about changes to hearing and vision, not attributes targeted by home
modifications.
What modifications were made
In order to understand what home modifications were made in the sample, home modification
data was analyzed in terms of where the modifications took place in the home, specifically the
bathroom, the kitchen or laundry, or as an access modification to help move in/ out/ through the
house. Given their broad variability (from a bath hand rail to an electric lift), they were considered
too variable to be typified according to type. Figure 23 compares the home modifications in each
location. Bathroom modifications were the most common in the sample (78.3%) followed by
modifications to help in moving through the home (61.8%) and, well behind in third place, kitchen
or laundry modification (4.4%).
International Journal of Architectural Research Phillippa Carnemolla, Catherine Bridge
Archnet-IJAR, Volume 10 - Issue 2 – July 2016 - (38-51) – Original Research Articles
Copyright © 2016 Archnet-IJAR, International Journal of Architectural Research
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Figure 3. Where home modifications were made in the home.
DISCUSSION
The research findings suggest the existence of a relationship between home modifications and
HRQoL, more specifically, they suggest that home modifications lead to an overall increase in
participants’ utility scores. Overall, with an average increase in utility score of 40 % after home
modifications were installed, this relationship is significant. This positive result in self-reported
wellbeing measures following home modification is reflected in two previous qualitative studies,
Andrich et al (1998) and Pettersson et al (2012).
Overall, there has been relatively little direct investigation into how home modifications
independently influence wellbeing measures such as HRQoL. Therefore, a major contribution of
this present research is the study of a single-factor home modification intervention with directly-
compared ‘before’ and ‘after’ HRQoL values.
When reviewing the sample demographics it becomes clear that people receiving home
modifications through government funded services are overwhelmingly owners of their own home
while receiving a government pension. The significance of a predominance of home owners is
that it signals an exclusion of private renters, possibly due to difficulties in authorizing home
modifications through landlords. This brings to light the need for research in this area in the
context of building and construction policy: how home modifications might be able to be better
provided to older people in a way that does not exclude private renters who are older or living
with a disability.
The utility dimensions
This is the first study to apply the Australian-developed and validated Assessment of Quality of
Life directly to changes in utility following home modifications, and therefore, the first time that the
utility dimensions have been explored from the perspective of home modifications.
International Journal of Architectural Research Phillippa Carnemolla, Catherine Bridge
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The findings relating to the utility dimensions as part of the overall utility score support the idea of
an overlapping suite of effects working in combination, all as a result of home modifications.
Increases were found to be statistically significant in three of the four utility dimensions:
Independent Living, Mental Health, and Relationships. The fact that the fourth utility dimension,
Senses, is least influenced by home modifications is unsurprising, given that, although home
modifications can improve the environment for hearing or vision, by improving light levels for
example, they cannot directly improve a person’s vision or hearing levels.
An implication of these findings in utility dimensions is that it reinforces the multi-layered
influence a home modification can exert in a hierarchy: firstly, providing independence, secondly,
impacting mental health, and thirdly, impacting relationships in the home.
Relating the study to Australian population norms of HRQoL and health of the sample
This study found that average self-reported measurements of HRQoL (measured as a utility
score) increased by 40%, from 0.3 before home modifications to 0.42 after home modifications.
This means that the sample population (whose average age was 72 years) sits well below the
Australian population norm of 0.76 for the compatible average age bracket (70-79) (Hawthorne et
al, 2013). The study sample is even further below the overall Australian population norm for all
age groups, which is 0.81. The lower average utility scores in this study can be explained, at least
in part, by the complex and serious health problems consistently found throughout the sample.
Being a sample drawn from the HACC-eligible population would suggest that the
participants were more likely to be frailer and have more co-morbidities than the equivalent-aged
non-HACC eligible population. It would be fair to consider that the sample represents a snapshot
within the Australian population who are likely to rely considerably on public health budgets and
community health services. The significant positive influence of home modifications on overall
HRQoL as well as the dimensional increases in Independent living, mental health, and
relationship is an important signaller for the value of our home environments to contribute to
public health and community services costs, such as caregiving for more vulnerable populations.
Indeed, further research within this wider study explores the influence of home modifications on
caregiving directly and is pending publication.
HRQoL and home modification location
The mapping of where home modifications were carried out in the home indicates that the
bathroom was the most common location at 78.3%, followed by general access modifications.
This tells us that the design of bathrooms has a significant role to play in maintaining levels of
independence and wellbeing in the houses of older people and those living with a disability. This
is unsurprising on two levels; first the nature of personal self-care tasks such as toileting and
washing are undertaken in the bathroom. Requiring care with these tasks can significantly impact
the nature of relationships in the home. Therefore, maintaining or restoring independence in the
bathroom not only restores the autonomy and ability of the person, but the care relationships in
the home. This is reflected in the increase in utility dimensions of Independent Living and
Relationships.
CONCLUSION
Implications of the research
Evidence from this research shows that home modifications have the potential to improve HRQoL
scores by 40%. Taking into consideration the exploratory nature of the research and the
possibility of recall bias in the self-reported results, the resulting data was found to be statistically
significant and the results remain compelling.
The results for the utility dimension data highlight the role home modifications can play in
influencing a number of different, yet overlapping wellbeing factors (independent living, mental
International Journal of Architectural Research Phillippa Carnemolla, Catherine Bridge
Archnet-IJAR, Volume 10 - Issue 2 – July 2016 - (38-51) – Original Research Articles
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49
health, and relationships) that, when combined, result in significant improvements in Health-
Related Quality of Life. There is supporting evidence for each of the overlapping factors, including
independence (Gignac, Cott, and Badley, 2000; Pettersson et al, 2012).
The contribution that the results of this study make to an understanding of housing and
health pathways are fourfold:
• It gathers primary housing and health data directly and concurrently, where previous evidence
has tended to be populated by less direct housing and health associations, due to multi-
factorial research, indirect health data, or estimated care data.
• It measures health from the perspective of the built housing domain, which is important for
future cross-disciplinary policy making.
• Given the lifespan of buildings, it focuses on rehabilitation or improving buildings to bring about
health improvements, as evidenced by the increase in HRQoL results following home
modification.
• It provides a basis from which to understand the broader health consequences of regulatory
and performance-based building codes relating to accessibility.
ACKNOWLEDGEMENTS
This work was supported by an Australian Postgraduate Awards (APA) Scholarship and a grant
from Australian Housing and Urban Research Institute (AHURI) in the form of a top-up
scholarship. We thank Mr. Fred Zmudzki, health economist and Director of Epoque Consulting,
for his advice regarding health related quality of life instruments. We also thank Angelo Iezzo,
Research Fellow, Centre for Health Economics at Monash University, for advice regarding how to
administration of the Assessment of Quality of Life Instrument within the research instrument in
this study.
REFERENCES
Adams, T., Bridge, C., Carnemolla, P., McNamara, N., and Quinn, J. (2014). Consumer factsheet:
Arranging home modifications consumer factsheet series (April 2014). Home Modification
Information Clearinghouse. www.homemods.info. Sydney, Australia: University of New South
Wales, Australia.
Aalto, A., Uutela, A., and Aro, A. (1997). Health related quality of life among insulin-dependent
diabetics: Disease-related and psychosocial correlates. Patient Education and Counseling, 30
(3), 215-225.
Ahmad, J., Shakil-ur-Rehman, S., and Sibtain, F. (2013). Effectiveness of home modification on
quality of life on wheelchair user paraplegic population. Rawal Medical Journal, 38 (3), 263-265.
Allen, T. (2005). Private sector housing improvement in the UK and the chronically ill: Implications for
collaborative working. Housing Studies, 20 (1), 63-80.
Andrich, R., Ferrario, M., and Moi, M. (1998). A model of cost-outcome analysis for assistive
technology. Disability and Rehabilitation, 20 (1), 1-24.
Bonnefoy, X. (2007). Inadequate housing and health: An overview. International Journal of
Environment and Pollution, 30 (3-4), 411-429.
Bratt, R. G. (2002). Housing and family well-being. Housing Studies, 17 (1), 13-26.
Braubach, M., and Power, A. (2011). Housing conditions and risk: Reporting on a European study of
housing quality and risk of accidents for older people. Journal of Housing for the Elderly, 25 (3),
288-305.
Brodsky, J., Habib, J., and Hirschfeld, M. (2003). Long-term care in developing countries: Ten case-
studies. World Health Organization.
Buck, H.G., Lee, C.S., Moser, D.K., Albert, N.M., Lennie, T., Bentley, B., and Riegel, B. (2012).
Relationship between self-care and Health-Related Quality of Life in older adults with moderate
to advanced heart failure. Journal of Cardiovascular Nursing, 27 (1), 8-15.
International Journal of Architectural Research Phillippa Carnemolla, Catherine Bridge
Archnet-IJAR, Volume 10 - Issue 2 – July 2016 - (38-51) – Original Research Articles
Copyright © 2016 Archnet-IJAR, International Journal of Architectural Research
50
Burns, N. (2004). Negotiating difference: Disabled people's experiences of housebuilders. Housing
Studies, 19 (5), 765-780
Carnemolla, P., and Bridge, C. (2012, February). How home modifications support ageing well at
home: Towards a lasting housing legacy. Paper presented at the 6th Australasian Housing
Researchers' Conference, Adelaide, Australia.
Carnemolla, P., and Bridge, C. (2015). Systematic review of home modification effects: Enabling built
environments program. Sydney, Australia: UNSW.
Gibson, M., Petticrew, M., Bambra, C., Sowden, A.J., Wright, K.E., and Whitehead, M. (2011).
Housing and health inequalities: A synthesis of systematic reviews of interventions aimed at
different pathways linking housing and health. Health and Place, 17 (1), 175-184.
Gignac, M., Cott, C., and Badley, E. (2000). Adaptation to chronic illness and disability and its
relationship to perceptions of independence and dependence. The Journals of Gerontology
Series B: Psychological Sciences and Social Sciences, 55 (6), 362-372.
Guyatt, G., Feeny, D., and Patrick, D. (1993). Measuring Health-Related Quality of Life. Annals of
Internal Medicine, 118 (8), 622-629.
Hawthorne, G., Korn, S., and Richardson, J. (2013). Population norms for the AQoL derived from the
2007 Australian National Survey of Mental Health and Well-being. Australian and New Zealand
Journal of Public Health, 37 (1), 7-16.
Heylighen, A. (2008). Sustainable and inclusive design: A matter of knowledge?. Local Environment,
13 (6), 531-540.
Imrie, R. (2003). Architects' conceptions of the human body. Environment and Planning D, 21 (1), 47-
66.
Jacobs, D.E., Brown, M.J., Baeder, A., Sucosky, M.S., Margolis, S., Hershovitz, J., and Morley, R.L.
(2010). A systematic review of housing interventions and health: Introduction, methods, and
summary findings. Journal of Public Health Management and Practice, 16 (5), S5-S10.
Liebig, P.S. (2000). Using home modifications to promote self-maintenance and mutual care: The
case of old-age homes in India. Physical and Occupational Therapy In Geriatrics, 16 (3-4), 79-
99.
Lin, M., Wolf, S., Hwang, H., Gong, S., and Chen, C. (2007). A randomized, controlled trial of fall
prevention programs and quality of life in older fallers. Journal of the American Geriatrics
Society, 55 (4), 499-506.
Patrick, D., and Erickson, P. (1993). Assessing Health-Related Quality of Life for clinical decision-
making quality of life assessment: Key issues in the 1990s. New York, N.Y.: Springer.
Pettersson, C., Löfqvist, C., and Malmgren Fänge, A. (2012). Clients' experiences of housing
adaptations: A longitudinal mixed-methods study. Disability and Rehabilitation, 34 (20), 1706-
1715.
Reeve, B.B., Wyrwich, K.W., Wu, A.W., Velikova, G., Terwee, C.B., and Snyder, C.F. (2013). ISOQOL
recommends minimum standards for patient-reported outcome measures used in patient-
centered outcomes and comparative effectiveness research. Quality of Life Research, 22, 1889-
1905.
Richardson, J., Peacock, S., Iezzi, A., Day, N., and Hawthorne, G. (2007). The assessment of quality
of life (AQoL) II instrument: Overview and creation of the utility scoring algorithm. Melbourne,
Australia: Monash University, Centre for Health Economics.
Sabia, J.J. (2008). There's no place like home: A hazard model analysis of aging in place among older
homeowners in the PSID. Research on Aging, 30 (1), 3-35.
Sullivan, M. (2003). The new subjective medicine: Taking the patient's point of view on health care
and health. Social Science and Medicine, 56 (7), 1595-1604.
Taylor, A. W., Price, K., Gill, T. K., Adams, R., Pilkington, R., and Carrangis, N. (2010). Multimorbidity
− not just an older person's issue: Results from an Australian biomedical study. BMC Public
Health, 10 (1), 718.
Thomson, H., Thomas, S., Sellstrom, E., and Petticrew, M. (2009). The health impacts of housing
improvement: A systematic review of intervention studies from 1887 to 2007. American Journal
of Public Health, 99 (S3), S681-S692.
International Journal of Architectural Research Phillippa Carnemolla, Catherine Bridge
Archnet-IJAR, Volume 10 - Issue 2 – July 2016 - (38-51) – Original Research Articles
Copyright © 2016 Archnet-IJAR, International Journal of Architectural Research
51
Thomson, H., Petticrew, M., and Morrison, D. (2001). Health effects of housing improvement:
Systematic review of intervention studies. BMJ: British Medical Journal, 323 (7306), 187.
Vernooij-Dassen, M.J., Osse, B.H., Schadé, E., and Grol, R.P. (2005). Patient autonomy problems in
palliative care: Systematic development and evaluation of a questionnaire. Journal of Pain and
Symptom Management, 30 (3), 264-270.
WHOQOL Group. (1993). Measuring quality of life: The development of the World Health Organization
Quality of Life Instrument (WHOQOL). Ginebra, Colombia: OMS.
__________________________________________________
AUTHORS
Phillippa Carnemolla
PhD, Research Associate
UNSW, Faculty of Built Environment
University of New South Wales, Sydney, NSW, Australia
Phillippa.carnemolla@unsw.edu.au
Catherine Bridge
Associate Professor
UNSW, Faculty of Built Environment
University of New South Wales, Sydney, NSW, Australia
