1. Housing Characteristics, Home Experiences and Community Engagement of People who Report Impairment

2. Authors and Acknowledgements
Authors: Craig Ravesloot PhD, Lillie Greiman MA, Bryce Ward, PhD, Andrew Myers Acknowledgements: This project is a collaboration between the RTC on Disability in Rural Communities at the University of Montana and the RTC on Community Living at the University of Kansas. Funding by: The National Institute on Disability, Independent Living, and Rehabilitation Research (NIDILRR)

3. Life starts at home….
Community participation is a central outcome in rehabilitation and independent living research.
People who report experiencing an impairment, participate less.
Qualitative research has highlighted how the home experience is linked to participation.
There is little quantitative research that examines home experience and community engagement.
Home is the springboard for community participation.
Difficulties within the home environment can present barriers to daily living that negatively impact an individual’s ability to participate in the community.
Increased energy spent on overcoming these problems in the home (such as lacking kitchen or bathroom access) may reduce time and energy for additional life pursuits such as employment, socialization and even relaxation.
Many of these difficulties within the home may also lead to increased risk of injury and other negative health impacts, both physical and psychological.

4. Home and Participation Background
The home should includes spaces that facilitate rest and rejuvenation (Mallett 2004)
“disabled people [sic] often experience the home as a series of ‘disembodied spaces’, or places that are designed in way that are rarely attentive to their physiological and bodily needs and functions” (Imrie, 2004)
Longitudinal research on disability and aging highlights that difficulties in the home may first be experienced in completing ADLs like dressing and bathing (Dunlop, Hughes, & Manheim (1997)
Intervention research in the bathroom focuses on fall and injury prevention, but not on participation outcomes (e.g., Gitlin, Miller & Boyce (1999).
Barriers in the home impact the broader participation of people with disabilities (Dunn 1990, Stineman et al 2007, Hammel et al. 2015).

5. Overview State of housing access (American Housing Survey)
Time use at home and in the community (American Time Use Survey)
Home experience and community engagement (Home Usability Survey)
Discussion and Conclusion
We set out to explore the linkage between home experience and community engagement.

6. State of housing access across the United States: 2011 AHS
Lillie Greiman
Research Associate
RTC: Rural

7. The American Housing Survey (AHS)
Sponsored by HUD and performed by the US Census
Provides a current and continuous series of data on housing across the US.
Conducted every two years
We used a sample collected for the 2011 AHS that included households with occupants between the ages of 18 and 75.
Complete sample redesign with 2015 survey
Survey started in Last survey redesign was in After the 2015 survey redesign no comparisons will be able be made with previous survey years.

8. Disability and Accessibility Variables in the AHS
2009 addition of the ACS (Census) disability indicators
2009 addition of the NOSTEP variable (presence of steps at entrance of unit)
“Outside, it is possible to enter this home/apartment WITHOUT climbing up or down any steps or stair? Please consider all entrances and ramps that could be used.”
2011 Housing Modification Module
Mobility equipment use
Functional limitation
Accessibility features
The housing modification module will be one of a set of rotating modules that will be featured in the survey year to year. We are not sure when the housing modification module will be featured again. However, as a result of the work we have done in the AHS looking at the module we have offered up some brief recommendations to HUD to clarify and improve some variables.

9. Rates of Inaccessible Housing
Features
Household member uses mobility equipment †
No household members use mobility equipment
Stepped Entrance
57.2%
60.9%
Up stairs with no elevator*
71.6%
81.7%
Inaccessible kitchen
66.8%
69.5%
Inaccessible bathroom
56.1%
60.2%
No grab bars in bathroom
62.3%
86.7%
No entry level bathroom**
18.5%
20.9%
No entry level bedroom**
32.4%
42.2%
Note these are households WITHOUT Accessibility features
† Cane, crutch, manual wheelchair, power wheelchair or scooter
* Of apartments
** Of units with more than one floor

10. Rate of Inaccessible Housing: Urban Rural Comparison
(Of HH with individuals using a mobility device)
* Of apartments
** Of units with more than 1 floor

13. Data limitations Defining “accessible” Rural/Urban data
No objective measurement (e.g.. 32” wide doorway, or outlets 15” off the floor)
Cognitive testing (DeMaio, T., & Freidus, R. 2011).
“Many respondents reported that aspects of their home could possibly be utilized by those in a wheelchair…this resulted in over-report of wheelchair accessibility features.”
Rural/Urban data
Inconsistent definitions: OMB definitions from 1980, 1990 and 2000 are used depending on the unit and when the unit was added to the survey.
Limited data available for rural areas
Respondents in both Round One and Round Two were generally not aware of the height of wheelchair-accessible electrical outlets or switches, or what they look like. Most respondents were also not aware of what wheelchair accessible kitchen cabinets, wheelchair accessible climate controls, or wheelchair accessible countertops are. Many respondents reported that aspects of their home could possibly be utilized by those in a wheelchair, though they were unsure whether their homes were designed with wheelchair accessibility in mind. Those respondents ended up saying “yes” to these questions. For example, one respondent said “yes” to having a wheelchair accessible kitchen because she felt her kitchen is big enough for someone in a wheelchair, even though she knows it was not designed to be wheelchair accessible. Some respondents reported having wheelchair accessible countertops because the height looked right, but didn’t consider that the wheelchair would have to be able to fit underneath. This resulted in over-report of wheelchair accessibility features.

14. Conclusions and implications
A large proportion of people with mobility impairments live in homes that do not meet their needs.
We see some rural-urban and regional variation in housing accessibility.
Significant numbers of households with individuals with mobility impairments have steps or even a flight of stairs at their home entrance.
Over half of households with individuals with mobility impairments do not have grab bars in their bathrooms.

15. Time use at home and in the community
Bryce Ward
Associate Director
Bureau of Business and Economic Research
University of Montana

16. Data: American time use Survey (ATUS)
87,000 observations; 2,800 with mobility impairment
3 Main questions:
What were you doing?
Where were you?
How long did you do this for?
(For some years for 3 random activities) How did you feel?
Data obtained from Sandra L. Hofferth, Sarah M. Flood, and Matthew Sobek American Time Use Survey Data Extract System: Version 2.4 [Machine-readable database]. Maryland Population Research Center, University of Maryland, College Park, Maryland, and Minnesota Population Center, University of Minnesota, Minneapolis, Minnesota.

17. Method
Compare time use for people with mobility impairments to time use for people without mobility impairments.
People with mobility impairments differ from people without mobility impairments (e.g., 90% of mobility impaired are out of labor force, 74% do not live with a spouse or partner, 67% are female, mean age is 63).
Thus we include controls for person characteristics (sex, age, education, employment, and school enrollment); family characteristics (number of kids, live with a partner, family income, own/rent home); location (region, MSA size); and interview (day of week, month, year, holiday).
Dependent measure (number of minutes in activity X) are skewed with lots of zeros, so we use GLM with log link and poisson distribution.

18. What do Mobility impaired do more/less of relative to similar non-mobility impaired?
Spend less time in “costly” activities. Spend more time in “cheap” restful activities.
Check specification – income, hhtenure, interactions.

19. Non-Mobility Impaired spend about 50% more time (47 min/day) on HH activities

20. For the mobility impaired, HH activities are associated with more pain, fatigue, and stress (but also more meaning)
Pain (z)
Tired (z)
Stress (z)
Happy (z)
Meaning (z)
HH Activities
0.06***
0.07***
0.01
-0.17***
-0.09***
(0.01)
Mobility Impairment
0.70***
0.30***
0.26***
-0.15***
-0.04
(0.04)
(0.03)
HH Activities * Mobility Impairment
0.07
0.08*
0.06
0.04
0.14**
(0.05)
Regression with individual random-effects of well-being measure (standardized) on indicators for doing a HH activity, mobility impairment, and the interaction of the two, plus controls for sex, age, education, employment, number of kids, marital status, how well they slept the night before, their cumulative exertion (MET) to that point in the day, interview day, interview month, interview year, holiday, metro/nonmetro, activity duration, activity start hour. Standard errors clustered on the individual in ( )’s.

21. Mobility Impaired spend about 10% More time (55 min/day) on Personal care activities (and 15%,121 min, more “resting”)

22. People with mobility impairments are less likely to report any time spent grooming, but those who groom spend more time Grooming.

23. People with mobility impairment are less likely to leave home and less likely to engage in social and recreational activities

24. The vast majority of people who go out/engage in social activities spend time grooming; however, people with mobility impairments are more likely to go out without grooming.

25. SO what does this suggest?
The facts are consistent with (but not definitive proof of) a simple economic story.
People have a certain capacity for effort (i.e., effort is scarce).
Every activity has an effort price. Effort price is determined by personal characteristics and environmental characteristics.
People with mobility impairments may have less capacity for effort, may face higher effort prices for activities, or both.
As such, they spend more time resting and less time engaged in activities – particularly activities with higher effort prices.
To increase activity/participation among people with impairments, need to increase capacity or lower prices of activities. This may be done through increasing personal capacity or by modifying the environment.
Lillie just discussed that homes vary in accessibility. I’m an economist, so I interpret that to mean that different houses impose different costs for certain activities, and this shapes choices. A decision to engage in a certain activity, is associated with a certain time cost, perhaps a monetary cost, but it also entails a certain cost in other finite resources like effort or energy. It is our belief that scarce effort frequently shapes individual choices – particularly for people with impairments. That is, for at least some activities
Is it house? Is it disability?
I am comparing people with impairment to non-impairment?
In some sense, we want to compare people with impairment across houses?
Describe then, explain.
I.e., if dropped the same person/family into different home environments, they would engage in different activities. E.g., put people in a home with a less accessible bathroom, and they may bathe less. Put people in a home with steps to get in and out, and they will leave the home less.
This is the larger question, we are interested in: to what extent to houses affect the price of different activities, and how are people’s choices respond when the price of activities change.

26. Home experience and community engagement
Andrew Myers
Research Associate
RTC: Rural

27. Introduction
A large proportion of people with mobility impairments live in homes that do not meet their needs and abilities.
People with mobility impairments spend less time washing, dressing, grooming and engaged in social activities.
How much do people with mobility impairments exert themselves in the home?
How does exertion relate to community engagement?
We often think of home as a place that should be safe and secure, a place of rest and relaxing where we recharge our bodies and minds, “home is where the heart is” as some say.
However, as Craig, and Lillie have shown, the general design of homes are not well suited to the needs and abilities of people with mobility impairments.
We also know from Bryce’s analysis that people with mobility impairment spend much less time bathing and engaged in social activities.
In this presentation we begin to bring these elements together to explore how experiences in the home are linked to the community. In the form of two guiding questions:
How much do people with mobility impairments exert themselves in the home?
How does exertion relate to community engagement?

28. Health and Home survey
Self-report survey to assess home usability, health, and participation developed with input from a team of CIL advisors
Demographics
Descriptive characteristics of the home
Exertion within the home (BORG Exertion Scale; % of maximum)
Number of social and recreation activities in the prior 7 days

29. Procedures General Population Sample:
Look at home usability across three urban communities using a random sample of approx. 2,500 address from zip codes surrounding local CILs in:
Atlanta, Georgia (33 Zips)
Fresno, California (25 Zips)
Indianapolis, Indiana (30 Zips)
Total Design Survey Method (Dillman)
Post cards to ID participants, surveys follow, reminder letters and priority surveys mailed
Random sample of approx. 2,500 address from zip codes surrounding local CILs*
Fresno: 25 zip codes, approx. 238,000 HH
Indianapolis: 30 zip codes, approx. 295,000 HH
Atlanta: 33 zip codes, approx. 313,000 HH
*Different geographies for each city to keep the sample populations similar

30. Sample Demographics (N=170)
Sex
Female
62%
Male
38%
Mean Age (Range)
60 (23-95)
Race and Ethnicity
White
African American
25%
Hispanic/Latino
13%
Asian 5%
American Indian 3%
Other 6%
Education
Less than high school
19%
High school/GED
23%
Some college/Assoc. degree
36%
Bachelors and higher
22%
Employment
Not employed
81%
Household Income
< $20,000
57%
$20,000-$60,000
26%
$60,001-$100,000
11%
>$100,000 6%
Were inputting data on Monday, analysis on Tuesday. This is very fresh data and surveys will continue to come in expanding the sample. This presentation is just a very small preliminary look into what this data may tell us.

31. Impairment and Health Impairment Walking 69% Errands 45% Dressing 38%
Memory
36%
Grasping
27%
Hearing
22%
Vision
17%
No Impairment
15%
Time with limitations (mean)
11.2 yrs.
Number of limitations (mean)
2.5
Equipment
Cane
40%
Walker
27%
Manual Wheelchair
15%
Brace
14%
Health
Excellent 4%
Very good
13%
Good
33%
Fair
39%
Poor
11%

32. Further, PWD report higher level of exertion across all activities throughout the home. Again, you’ll notice that bathing and cleaning are both near the top. With bathing, PWD report over 3x more exertion than people without.
No Mobility Impairment:
13 Deaf
8 Blind
9 Cognitive
4 Self-Care
9 IL
5 Grasping
(27 some type of other impairment)
(26 no impairment at all)
(1 no answer)
Mobility Impairment:
25 Deaf
20 Blind
49 Cognitive
60 Self-Care
66 IL
40 Grasping

33. Bathroom Characteristics
Mobility Impairment %
No Mobility Impairment %
Can enter bathroom
97%
100%
Can open/close bathroom door
90%
98%
Can use/reach bathroom sink
95%
Can get in/out of shower/tub
72%
93%
Has toilet grab bars
28%
15%
Has shower/tub grab bars
39%
32%
Needs toilet grab bars
41%
17%
Needs shower/tub grab bars
50%
22%

34. The results above highlight, individuals with impairment experience more exertion while participating in activities within their homes, particularly while bathing,
…but does it matter? Is exertion associated with other aspects of their daily lives?

35. GLM Regression of Bathing Exertion on Social/Recreation Activities (n=159)
Variables
IRR SE z p
95 CI
Bathing exertion
0.74
0.07
-2.97
0.003
0.613; 0.905
Mobility impairment
0.62
0.11
-2.69
0.007
0.433; 0.877
Subjective Health (excellent excluded)
Very Good
0.54
0.27
-1.21
0.226
0.203; 1.457
Good
0.55
0.211; 1.445
Fair
0.61
0.30 -1
0.318
0.233; 1.606
Poor
0.39
0.23
-1.58
0.114
0.123; 1.253
White
0.76
0.13
-1.63
0.104
0.551; 1.507
Partnered
0.64
0.16
-1.79
0.074
0.388; 1.044
Lives with other people
1.40
0.26
1.81
0.973; 2.012
Constant
10.90
5.51
4.72
4.044;
Note: IRR= Incidence rate ratio; SE= standard error; Analysis completed using generalized linear model with a log link and a Poisson distribution
Attached are the results for the analysis that regresses number of social activities on bathroom exertion excluding the outlier (observation 58C).  These results include controls for mobility impairment, health status, race, whether the person has a partner, and whether there are other people in the HH. Adding additional controls for age, gender, income does not affect the results. The included controls costs us 20 observations (due to missing data) and shrinks the coefficient by a non-trivial amount.  The reduction could be due to controls or could reflect the lost observations.    
This analysis uses GLM (generalized linear models) with a log link and a poisson distribution.  This is a common method for dealing with data like ours (count data with lots of zeros).  \
Note, I present exponentiated coefficients (or an incidence rate ratio).  You interpret these similar to an odds ratio.  So, the attached results mean that a one standard deviation increase in bathroom exertion is associated with a 35 percent (1/0.74) decrease in the number of observed social activities.  (Note: excluding the controls changes the result so that 1 s.d. increase in exertion is associated with a 61 percent decrease in social activities.)  
A one standard deviation increase in bathing during the prior week.”  The only statistical control that is significant is mobility impairment.  exertion is associated with a 35% decrease in the likelihood that the individual reports engaging in any social/recreation activities Without controls, there is a 61% decrease in social/recreation activities for each unit increase in bathing exertion.
Control demographics %:
Has partner: 32.3%
Lives with other people: 62.3%

36. Summary & Implications
People with mobility impairments exert themselves in home activities more than people without mobility impairment.
Exertion while bathing is related to perceived need for shower bars
Level of exertion bathing is related to the number of social and recreation activities

37. Discussion and Conclusions
Many people with mobility impairment live in homes that are not accessible.
People mobility impairment spend their time differently from people without mobility impairment.
People with mobility impairment are less likely to bathe and less likely to leave home than people without mobility impairment.
Level of exertion bathing is related to the number of social and recreation activities

38. For Your Consideration…
How might reducing exertion in the home increase opportunities and choices for participation?
How might exertion in the home be reduced?
Assistive equipment (e.g., grab bars, shower chairs)
Get people into more usable homes

39. Contact Craig Ravesloot, PhD 52 Corbin Hall University of Montana
Missoula, MT 59812
The Home Usability Network Intervention (
Home Usability Network
Working with CIL in the three surveyed communities to develop home usability networks to address home usability needs for individuals who are participating in the project.
Home Usability Networks are local coalitions that work together to contribute resources, materials and expertise toward addressing the home usability needs of those living in their communities.