More than Independence: The Contribution of Mobility to Quality of Life in Older

Persons

More than Independence: The Contribution of Mobility to Quality of

Life in Older Persons

Steve La Grow, Polly Yeung, Andy Towers, Fiona Alpass & Christine Stephens

Health and Ageing Research Team

Massey University

• Traditionally, the goal of vision rehabilitation has been to restore independence in function to the level enjoyed before the onset of significant vision impairment.• A goal which has particular resonance for O&M

ensuring its place as an integral component of any vision rehabilitation program

• While the restoration of independence may still be the primary goal for providing rehabilitation services to working age adults, • the goal of rehabilitation for older adults

is more likely to be related to the promotion of successful aging than the restoration of independent function.

• A focus on the promotion of successful aging makes the outcomes of vision rehabilitation programs more congruent with the goals of a broader range of funding bodies as there are many initiatives underway to promote successful aging, such as • the World Health Organization’s Active

Aging and Age-Friendly Cities initiatives,• OECD’s Reforms for an Aging Society• Australia’s National Strategy on Aging• New Zealand’s Positive Aging Strategy

• This change in emphasis reflects a changing view of the importance of successful aging in aging societies and a fear of the cost of unsuccessful aging to those societies.• Most countries are now faced with a

rapidly aging population and are seeking ways to allow their citizens to live longer, happier, healthier lives, while remaining productive, independent and at home for as long as possible.

• Defining successful aging, however, has proved to be a bit more difficult than wishing to promote it.• Variously referred to as

• successful aging, • positive aging, • healthy aging • active aging

• Early definitions focused on the absence of chronic illness and disability, as well as, exceptional longevity.

• This was found to be a relatively narrow focus, • not terribly helpful for addressing the

issues raised at governmental level by an aging society • and not particularly congruent with the

views of older people themselves.

• Older people were found to value subjective measures of perceived QOL more than objective measures of health, with the vast majority of those identifying themselves as successful agers having at least one chronic illness or functional limitation.• As a result PQOL has generally become to be

seen as an essential component of successful aging.

• We were particularly interested in determining the extent to which mobility affected PQOL among those who report having difficult seeing to determine the role O&M may have in a rehabilitation paradigm focused more on promoting successful aging than on restoring independence.

To answer this question, we conducted a study in which we used standard multiple regression to investigate the extent to which variance in PQOL would be predicted from 8 variables thought to impact on QOL (La Grow, Alpass, Stephens & Towers, 2011).

These variables were

• Satisfaction with ability to perform activities of daily living

• Ability to get around (mobility)

• Economic Standard of Living

• Total number of diagnosed health conditions

• Physical health status

• Mental health status

• Social isolation

• Satisfaction with life

• 265 older adults who reported having difficulty with seeing ordinary news print even when wearing glasses or contact lenses were drawn from the first wave of the New Zealand Health, Work and Retirement Longitudinal Study were the focus of analysis for this investigation.

Overall Model and variables entered as predictors of PQOL

Model Adjusted R2 = 0.64

F = 57.26, p < 0.001

Variables entered

β

p

Satisfaction with ADL 0.031 0.597 Ability to get around 0.307 <0.001** Economic standard of living 0.089 0.055 Total number of diagnosed health conditions

0.108 0.022*

Physical health status 0.040 0.481 Mental health status 0.055 0.303 Social isolation 0.045 0.323 Satisfaction with life 0.439 <0.001**

• We found that together these 8 variables predicted 64% of the variance observed in PQOL• Three were found to make a unique and

significant contribution to that prediction• Satisfaction with life (β = 0.439, p < 0.001 )• Ability to get around (β = 0.307 p < 0.001 )• Total number of diagnosed health conditions (β = 0.108 p = 0.022)

• While these findings were useful, • The method used lacked sufficient

sophistication to indicate how these variables might combine or interact to affect PQOL• The single-item measure of satisfaction

with life used may be too imprecise to shed much light on the ways various aspects of satisfaction with life might impact on PQOL.

• As a result, we conducted another study • which employed structural equation

modelling to gain a more sophisticated view of the interactions which may exist among variables, and • Used factor analysis and confirmatory

factor analysis to form discrete constructs from a 11-item measure of life satisfaction (Yeung, La Grow, Towers, Alpass & Stephens, 2011).

• 356 older adults who reported having difficulty with seeing ordinary news print were drawn from the 2nd wave of the New Zealand Health, Work and Retirement Longitudinal Study were the focus of analysis for this investigation.

How Satisfied are you with…..Content Factor 1 Factor 2 Factor 3

Your ability to perform activities of daily living?

0.86

0.39

0.33

Your capacity to work? 0.83 0.40 0.40

Your health? 0.82 0.38 0.37

Yourself? 0.68 0.43 0.53

Your sleep? 0.57 0.22 0.40

Your transport? 0.42 0.77 0.15

Your access to health services? 0.32 0.76 0.27

The conditions of your living space? 0.41 0.73 0.41

Your personal relationships? 0.42 0.38 0.82

Your sex life? 0.47 0.20 0.74

The support you get from your friends? 0.33 0.57 0.58

• Resulted in a 3-factor solution, with good construct validity, and goodness of fit indices that were better than those found for a 1-factor solution reflecting the simple summation of all 11 items (e.g. M = 0.93 v M = 0.80)

• Factor 1 = Satisfaction with functional capacity

• Factor 2 = Satisfaction with life essentials

• Factor 3 = Satisfaction with personal relationships

• We used structural equation modelling and proposed two models to predict PQOL consisting of 5 independent variables reflecting but expanding on the three (number of diagnosed health conditions, satisfaction with life and ability to get around) found to make significant contributions in the earlier study• 1. a linear model • 2. an interactive model

• 5 independent variables• Number of diagnosed health conditions• Satisfaction with functional capacity• Satisfaction with life essentials• Satisfaction with personal relationships• Ability to get around

• and 1 dependent variable • PQOL

Model 1: a linear model

Satisfaction with Functional Capacity

Satisfaction with Personal

Relationships

Quality of Life (R2 = 0.57)

Number of Health Conditions Reported

Ability to Get Around

Satisfaction with Life Essentials

0.19***

0.18**

0.09

0.40***

-0.04

• This model parallels the linear results found earlier (La Grow, Yeung, Towers, Alpass & Stephens, 2011).

• The model predicted 57% of the variance in PQOL• Three independent variables were found

to make a significant and unique contributions to that prediction.

• They were: • Satisfaction with functional capacity

(0.40)• Ability to get around (0.19)• Satisfaction with personal relationships

(0.18)

• We then proposed a non-linear model in which the factors involved were expected to interact with one another and ultimately with PQOL and compared the two on goodness of fit.

Model 2: an interactive model

0.48***

0.45***

0.34***

0.42*** 0.59***

-0.10

-0.02

-0.25***

0.62*** 0.39***

Satisfaction with Personal

Relationships (R2 = 0.16)

Quality of Life (R2 = 0.57) Satisfaction with Life

Essentials (R2 = 0.18)

0.19**

0.19***

0.09

0.40***

-0.04 Number of Health

Conditions Reported

Ability to Get Around

Satisfaction with Functional Capacity

(R2 = 0.54)

We found that the second model predicted the same amount of variance in PQOL as the first but had better goodness of fit indices than that of the first model and therefore more explanatory of the two models

Fit Index Model 1 (linear) Model 2 (interactive)

Χ2/df 124.42/62 105.55/61RMSEA 0.05 0.05GFI 0.95 0.96AGFI 0.92 0.93CFI 0.97 0.98

We found the second to be more informative than the first by giving us an understanding of the direct, indirect and total effects of each variable/construct assessed on

PQOL

scale Satisfaction with functional capacity

Ability to get around

Satisfaction with personal relationships

Satisfaction with life essentials

Total number of diagnosed health conditions

PQOL Direct effect Indirect effectTotal effect

0.400.120.52

0.190.34

0.53

0.19----

0.19

0.090.09

0.18

-0.04-0.12-0.16

• The take home message here is that mobility (ability to get around) and satisfaction with functional capacity had nearly equal total effects on PQOL

• These two were responsible for almost all the effect seen

• Mobility was found to have both a direct impact on PQOL and contributed to the impact satisfaction with functional capacity and satisfaction with personal relationships had on PQOL as well

• This should also answer the question: What is the place of O&M in a vision rehabilitation program which seeks to promote successful aging as a goal.

• The results of this study would indicate that it would be as integral a component of such a program as it is for programs designed to restore independence following the onset of significant vision impairment.

What about older adults in general?

• That brought us to a new question• Is mobility also an important

consideration in the PQOL of older people in general or are these results unique to those who have difficulty seeing?

• We addressed that question by replicating the study I have just described by using all 2473 older adults from the 2nd wave of the New Zealand Health, Work and Retirement Longitudinal Study (La Grow, Yeung, Towers, Alpass &

Stephens, 2013).

.

• We again ran the factor analysis and confirmatory factor analysis on the 1-item satisfaction with life measure to determine if we would find the same 3-factor solution for satisfaction with life with this population as we found in the smaller sample of those who had difficulty seeing.

• We did.

How satisfied are you with……Content Factor 1 Factor 2 Factor 3

Your ability to perform activities of daily living?

0.85

0.23

0.12

Your capacity to work? 0.84 0.22 0.07

Your health? 0.78 0.22 0.18

Yourself? 0.64 0.22 0.44

Your sleep? 0.52 -0.01 0.27

Your transport? 0.22 0.79 0.07

Your access to health services? 0.16 0.77 0.12

The conditions of your living space? 0.19 0.67 0.30

Your personal relationships? 0.25 0.22 0.79

Your sex life? 0.21 0.03 0.77

The support you get from your friends?

0.09

0.37

0.589

• As a result, we assessed the same two models as we did before, the linear and interactive models and got similar results. • Both models were found to predict 52% of

the variance in PQOL • similar to but somewhat less than the 57% predicted in the earlier study.

Model 1: a linear model

0.19***

0.17***

0.32***

0.18***

-0.02

Quality of Life (R2 = 0.52)

Mobility

Satisfaction with Functional Capacity

Satisfaction with Life Essentials

Satisfaction with Personal

Relationships

Total Health Conditions

The linear Model

• In this case, four variables were found to make a unique and significant to the prediction of variance in PQOL, they were:• Satisfaction with functional capacity (0.32)• Satisfaction with personal relationships

(0.19)• Ability to get around (Mobility) (0.18)• Satisfaction with life essentials (0.17)• in that order.

• We proposed the same non-linear model in which the factors involved were expected to interact with one another and ultimately with PQOL • and assessed and as before assessed that

for goodness of fit.

Model 2: an interactive model

-0.02

-0.22***

-0.29***

-0.29***

-0.19***

-0.41***

0.15***

0.19***

0.16***

0.36***

0.70***

0.25***

0.83***

0.10***

0.68***

Satisfaction with Personal

Relationships (R2 = 0.47)

Quality of Life (R2 = 0.52)

Satisfaction with Life Essentials (R2 = 0.40)

Satisfaction with Functional Capacity

(R2 = 0.61)

Total Health Conditions

Mobility

Fit Index Model 1 (linear) Model 2 (interactive)

Χ2/df 508.07/58 246.45/54RMSEA 0.06 0.04GFI 0.97 0.99AGFI 0.95 0.99CFI 0.97 0.99

As before, we found that the second model predicted the same amount of variance in PQOL as the first but had better goodness of fit indices and therefore was once again accepted as the more explanatory of the two

In this case, we found that satisfaction with functional capacity had both the greatest direct and total effect on PQOL but that ability to get around had the greatest indirect effect and 2nd greatest total effect.

scale Satisfaction with functional capacity

Ability to get around

Satisfaction with personal relationships

Satisfaction with life essentials

Total number of diagnosed health conditions

PQOL Direct effect Indirect effectTotal effect

0.350.310.66

0.150.350.50

0.19-----0.19

0.160.050.21

-0.02-0.09-0.11

• From this we would conclude that mobility has a major impact on older persons perception of PQOL and should therefore be considered an essential element in any program designed to enhance PQOL and ultimately successful aging in this population.

• As a result, we would also conclude that mobility interventions should be considered for programs designed to promote successful aging among older adults, especially for those who have difficulty seeing but more generally and in somewhat different forms across the population as a whole.

Acknowledgements• I’d like to thank• Dr Polly Yeung, Dr Andy Towers, Professor

Fiona Alpass and Professor Christine Stephens, the co-authors of this presentation for their collaboration on this project and various studies described here• The Health Research Council of New

Zealand for funding the Health, Work and Retirement Longitudinal Studies• And the participants who have answered

our questions repeatedly over time.

References• La Grow, S., Alpass, F., Stephens, C. & Towers, A. (2011).

Factors affecting perceived quality of life of older persons with self-reported visual disability. Quality of Life Research, 20, 407-413.

• Yeung, P., La Grow, S., Towers, A., Alpass, F. & Stephens, C. (2011). The centrality of O&M in rehabilitation programs designed to enhance quality of life: A structural equation modelling analysis. International Journal of Orientation & Mobility.4, 10-20.

• La Grow, S., Yeung, P., Towers, A., Alpass, F. & Stephens, C. (2013). The Impact of mobility on quality of life among older persons. Journal of Aging and Health, 25 (5), 723-736.