Group Title: BMC Public Health
Title: Age at disability onset and self-reported health status
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Title: Age at disability onset and self-reported health status
Physical Description: Book
Language: English
Creator: Jamoom, Eric
Horner-Johnson, Willi
Suzuki, Rie
Andresen, Elena
Campbell, Vincent
The RRTC Expert Panel on Health Status Measurement
Publisher: BMC Public Health
Publication Date: 2008
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Abstract: BACKGROUND:The critical importance of improving the well-being of people with disabilities is highlighted in many national health plans. Self-reported health status is reduced both with age and among people with disabilities. Because both factors are related to health status and the influence of the age at disability onset on health status is unclear, we examined the relationship between disability onset and health status.METHODS:The U.S. 1998–2000 Behavioral Risk Factor Surveillance system (BRFSS) provided data on 11,905 adults with disability. Bivariate logistic regression analysis modeled the relationship between age at disability onset (based on self-report of duration of disability) and fair/poor self-perceived health status, adjusting for confounding variables.RESULTS:Key variables included demographics and other measures related to disability and general health status. Disability onset after 21 years of age showed significant association with greater prevalence of fair/poor health compared to early disability onset, even adjusting for current age and other demographic covariates. Compared with younger onset, the adjusted odds ratios (OR) were ages 22–44: OR 1.52, ages 45–64: OR 1.67, and age =65: OR 1.53.CONCLUSION:This cross-sectional study provides population-level, generalizable evidence of increased fair or poor health in people with later onset disability compared to those with disability onset prior to the age of 21 years. This finding suggests that examining the general health of people with and those without disabilities might mask differences associated with onset, potentially relating to differences in experience and self-perception. Future research relating to global health status and disability should consider incorporating age at disability onset. In addition, research should examine possible differences in the relationship between age at onset and self-reported health within specific impairment groups.
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Research article

Age at disability onset and self-reported health status
Eric W Jamoom* 1, Willi Horner-Johnson2, Rie Suzuki2, Elena M Andresen1,
Vincent A Campbell3 and the RRTC Expert Panel on Health Status
Measurement2


Address: 'College of Public Health and Health Professions, University of Florida, PO Box 100231 Gainesville, FL 32610, USA, 2RRTC: Health &
Wellness, Oregon Health & Science University, CDRC PO Box 574, Portland, OR 97207, USA and 3National Center on Birth Defects and
Developmental Disabilities, Centers for Disease Control and Prevention, 1600 Clifton Rd.; MS-E-88; Atlanta GA 30333, USA
Email: Eric W Jamoom* jamoom@phhp.ufl.edu; Willi Horner-Johnson homerjo@ohsu.edu; Rie Suzuki suzukir@ohsu.edu;
Elena M Andresen andresen@phhp.ufl.edu; Vincent A Campbell vbc6@cdc.gov; the RRTC Expert Panel on Health Status
Measurement wingenfe@ohsu.edu
* Corresponding author



Published: 9 January 2008 Received: 19 March 2007
BMC Public Health 2008, 8:10 doi: 10.1 186/1471-2458-8-10 Accepted: 9 January 2008
This article is available from: http://www.biomedcentral.com/1471-2458/8/10
2008 Jamoom et al; licensee BioMed Central Ltd.
This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0),
which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.



Abstract
Background: The critical importance of improving the well-being of people with disabilities is
highlighted in many national health plans. Self-reported health status is reduced both with age and
among people with disabilities. Because both factors are related to health status and the influence
of the age at disability onset on health status is unclear, we examined the relationship between
disability onset and health status.
Methods: The U.S. 1998-2000 Behavioral Risk Factor Surveillance system (BRFSS) provided data
on 11,905 adults with disability. Bivariate logistic regression analysis modeled the relationship
between age at disability onset (based on self-report of duration of disability) and fair/poor self-
perceived health status, adjusting for confounding variables.
Results: Key variables included demographics and other measures related to disability and general
health status. Disability onset after 21 years of age showed significant association with greater
prevalence of fair/poor health compared to early disability onset, even adjusting for current age and
other demographic covariates. Compared with younger onset, the adjusted odds ratios (OR) were
ages 22-44: OR 1.52, ages 45-64: OR 1.67, and age >65: OR 1.53.
Conclusion: This cross-sectional study provides population-level, generalizable evidence of
increased fair or poor health in people with later onset disability compared to those with disability
onset prior to the age of 21 years. This finding suggests that examining the general health of people
with and those without disabilities might mask differences associated with onset, potentially relating
to differences in experience and self-perception. Future research relating to global health status and
disability should consider incorporating age at disability onset. In addition, research should examine
possible differences in the relationship between age at onset and self-reported health within specific
impairment groups.






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Background
"Disability is an issue that affects every individual, com-
munity, neighborhood, and family..."[1] People can
acquire disabilities at any point in their lives. Of critical
importance is the ability to develop or maintain a high
quality of life after the acquisition of a disability [2].
Health related quality of life (HRQOL) is included as an
overarching aspect of the American health strategic plan,
Healthy People 2010, which is a set of national health
objectives that encourages the use of self-rated health as a
measure to evaluate health status in the population. Pop-
ulation-based surveillance of general health status moni-
tors progress of two overall goals from Healthy People
2010: 1) to increase the quality and years of healthy life,
and 2) to eliminate health disparities [3]. Surveillance
questions on HRQOL can be used to examine different
outcomes for people with and without disabilities and
detect possible disparities [4]. However, even within spe-
cific impairments and diagnoses, people with disabilities
report a broad range of self-reported health on com-
monly-used measures [5].

Factors that may impact self-reported health status
include severity of disability or health condition, type of
activity limitation, and age of the person with the disabil-
ity [2,6]. Further, in what has been referred to as the "dis-
ability paradox", people with serious and persistent
disabilities often report experiencing a good or excellent
quality of life when to others it would appear that their
health is poor [7]. This seeming paradox may be related to
adoption of a positive disability minority group identity
[8] or to a tendency on the part of outside observers to
equate poor health with disability while people with dis-
abilities may view them as separate constructs [9]. Age at
onset of a disability, as well as the duration of the disabil-
ity, can also impact health status [10]. Individuals who
acquire a disability later in life may be more likely to rate
their global health status in relation to their perceived
health prior to the disability and have greater difficulty
adjusting to the disability [ 11 ]. In contrast, early disability
onset and longer duration of disability may allow greater
adjustment to the disability both in terms of psychosocial
identity development and adoption of coping strategies,
leading to higher reported general health [12,13]. Evalua-
tion of general health itself also may be adjusted to reflect
changing standards and values in response to disability
[12,14,15].

Empirical evidence supports the view that self-reported
health status is related to age at onset and duration of dis-
ability. For example, people with congenital deafness
have reported better health status than people with later
onset deafness [16,17]. In people with spinal cord injury
(SCI), both increasing age with SCI and more advanced
age at injury onset have been associated with higher


depression levels and poorer self-perceived health [18].
Other disease specific studies suggest earlier age onset is
associated with better reported health status, even
accounting for advancing age [10,19]. However, the over-
all relationship between age at onset and health status in
broad population-based disability groups (e.g., among
people with activity limitations or who use special equip-
ment) has not been fully characterized. If the age that dis-
ability is acquired is associated with perceived general
health, this knowledge might assist in more sensitive
measurement of health, as well as in developing tailored
interventions and interpreting heterogeneous age-related
effects on general health status.

We analyzed data from the USA Behavioral Risk Factor
Surveillance System (BRFSS) 1998-2000 to assess the
relationship between disability onset and self-reported
health status, a common measure of global health [20].
Specifically, we asked if general health status differs for
people with different ages of disability onset, while con-
trolling for possible confounders.

Methods
The BRFSS is a state-based telephone (random-digit-
dialed) survey of the noninstitutionalized U.S. popula-
tion aged 18 years of age and older that provides data
related to chronic diseases and their risk factors [21,22].
The BRFSS uses a Disproportionate Stratified Sample
(DSS) method, where phone numbers are randomly
selected throughout the state, business and nonworking
numbers are omitted, and individuals aged 18 years and
older are randomly selected from each household called.
Data are subsequently weighted to reflect the complex
sampling methods and nonresponse bias of the final sam-
ple [23]. This survey provides annual population-based
cross-sectional data that can be used to analyze self-
reported risks and health conditions. The BRFSS includes
national "core" questions and modules, and state-added
modules on special topics of interest to specific states. The
BRFSS has previously been used to identify prevalence
and correlates of general health among people with disa-
bilities [5,24].

The present study analyzed data from the seven states and
the District of Columbia that used both the core BRFSS
Healthy Days measures (CDC HRQOL-4) and the
HRQOL/Disability module each year from 1998-2000.
The states (Arkansas, Iowa, Kansas, New York, North
Carolina, Rhode Island, and South Carolina) and the Dis-
trict of Columbia represent a wide selection of the U.S.
population. The total BRFSS sample size across all three
years was 73,867. For the eight sites used in the study,
response rates ranged from 52.2% (New York) to 75.1%
(Kansas) with a median of 61.3% in 1998; in 1999, the
range was 45.0% (New York) to 66.3% (Kansas) with a


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median of 48.7; in 2000, response rates ranged from
32.9% (New York) to 59.3% (North Carolina) with a
median of 40.8% (see 2000 Behavioral Risk Factor Sur-
veillance System Report [25] for response rates for each
state in each year). For these analyses, we limited the sam-
ple to respondents who were classified as having a disabil-
ity and answered a question on their disability duration (n
= 11,905). Our working definition of disability was based
on respondents saying "yes" to either of two questions:
"Are you limited in any way in any activities because of
any impairment of health problem?" or "Do you now
have any health problem that requires you to use special
equipment, such as a cane, a wheelchair, a special bed, or
a special telephone?"

For this study, the dependent variable of self-reported
general health status was classified as a dichotomous var-
iable (fair/poor vs. excellent/very good/good), based on
answers to the question "Would you say that in general
your health is excellent, very good, good, fair, or poor?"
This question is included in the CDC HRQOL-4, along
with three questions about the number of recent days of
the last 30 when physical health was not good, mental
health was not good, and activities were limited because
of poor health. The CDC HRQOL-4 questions have been
demonstrated to predict morbidity, health care use, and
mortality and are associated with chronic diseases and
disability [26-28]. The retest reliability of HRQOL ques-
tions is moderate to excellent [4]. The questions also have
demonstrated reliability and validity for population
health surveillance [4,28,29] and people with disability
[301.

The primary predictor variable for these analyses was age
at disability onset, computed from questions on self-
reported disability duration and current age. Respondents
who answered yes to one or more of the disability screener
questions above were asked how long their activities had
been limited. Responses were given in days, weeks,
months, or years. These responses were recorded by the
authors to indicate the number of years, or portions of a
year (in decimal format), activities had been limited. This
disability duration variable was subtracted from the
respondent's current age on the date of the interview to
determine the respondent's age at the time of disability
onset. Age at disability onset was then categorized into
four groups: birth through 21 years of age, ages 22 to 44,
ages 45-64, and age 65 years or older. We classified early
disability onset as birth through age 21 years based on
federal laws designating developmental disability services
for individuals aged 0-21 years. Adult onset was consid-
ered age 22 years and older; the additional divisions
within this age range were made to allow examination of
potential effects of early adult versus older adult disability
onset. Thus, there were four groups classified by differing


ages at disability onset, based on information reported at
time of interview.

In addition, we included a set of potential confounding
variables: age (as a continuous variable); gender; race/eth-
nicity (white non-Hispanic, African American non-His-
panic, other non-Hispanic groups, and all Hispanics);
current employment status (employed, unemployed, stu-
dent/homemaker, retired, unable to work); education (<
high school graduate vs. > high school graduate); marital
status (married, separated/divorced, widowed, never mar-
ried); and disability duration (years limited as a continu-
ous variable).

Descriptive analyses compared characteristics of all four
disability onset groups and respondents who were classi-
fied as not having a disability. Logistic regression models
with health status as the outcome report odds ratios (OR)
and 95% confidence intervals (95% CI) for people with
disabilities only. Models were constructed by forcing in
age at onset as the primary predictor variable, and includ-
ing additional variables if they had a meaningful effect on
the odds ratio of age at onset (10% or more change in OR)
or if the variable itself was a significant predictor of gen-
eral health status. We performed an exploratory analysis
to investigate whether the relationship of age at onset and
health status might be different for men versus women by
adding an interaction term between gender and age at
onset, but the interaction was non-significant. An interac-
tion of age and disability duration was also tested; there
was no significant interaction (data available on request).
Thus, results are provided for main effects only. Descrip-
tive results were analyzed using SUDAAN 9.0.0 (Research
Triangle Institute, Research Triangle Park, NC, 2004) for
weighted data, and logistic regression was conducted with
SPSS Complex Samples 14.0 for Windows (SPSS, Inc.,
Chicago, IL, 2005). Stratification and weighting variables
related to the BRFSS sampling and weighting strategy were
included in the analyses as design variables. This study
was approved by the Institutional Review Boards at the
University of Florida and Oregon Health & Science Uni-
versity.

Results
There were 11,905 respondents who were classified as
having a disability, which yielded a population estimate
of 4,370,174 adults with disability for the seven states and
the District of Columbia. These included people with
computed disability onset between birth and age 21 years
(raw n = 1,272), ages 22 and 44 (n = 4,085), ages 45 and
64 (n = 3,906), and age 65 years or older (n = 2,642).
Table 1 compares characteristics of these groups and
58,483 adults who were not classified as having a disabil-
ity. In general, these figures demonstrate a trend of
increasing fair or poor reported health status across the


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Table I: Sample characteristics by age at onset


Age at disability Onset Groups


>65 No Disability


Sample Size n = 1,272


Estimated Population


Variables


Self-reported general health status:
Fair or poor health (Age Adjusted)
Mean disability limitation years (sd)
Mean current age (sd)
Current age > 65

Gender: female
Race:
White, non-Hispanic
Black, non-Hispanic
All Hispanic
Other
Income (n = 58,784): <$25000
Education: HS graduate or above
Marital status:
Married or unmarried couple
Separated or divorced
Widowed
Never been married
Employment status (n = 70,306):
Employed or self-employed
Unemployed
Retired
Student or homemaker
Unable to work


557,969


n = 4,085

1,550,869


n = 3,906 n = 2,642 n = 58,483 n = 70,388


1,401,986


859,351


23,673,140 28,043,314


Perce (SE) Perce (SE) Perce (SE) Perce (SE) Perce (SE) Perce (SE)
nt nt nt nt nt nt


24.59 2.16 40.72 1.48 52.64 1.46 55.97 1.88 9.02 0.23 14.18 0.24
23.28 0.94 9.21 0.29 6.93 0.18 3.75 0.12
35.22 0.77 43.26 0.30 60.87 0.25 77.14 0.24 43.72 0.13 45.42 0.12
5.46 1.01 4.34 0.48 32.43 1.39 100.0 0.00 15.31 0.26 17.98 0.26
0
48.77 2.53 52.57 1.47 58.28 1.45 66.13 1.75 51.61 0.38 52.38 0.35

73.53 2.44 75.06 1.44 78.59 1.30 85.49 1.53 74.44 0.36 75.00 0.33
14.09 1.83 12.55 0.98 12.27 0.92 9.54 1.23 13.73 0.26 13.47 0.24
8.23 1.77 8.98 1.19 6.55 0.93 4.03 0.95 7.95 0.27 7.82 0.24
4.15 1.12 3.41 0.59 2.59 0.58 0.94 0.46 3.88 0.18 3.71 0.16
42.01 2.63 40.80 1.46 49.59 1.59 61.37 2.19 26.87 0.37 30.05 0.34
83.44 1.85 85.91 0.97 76.14 1.23 71.50 1.63 88.83 0.26 87.40 0.24

46.53 2.51 59.62 1.40 62.97 1.34 44.69 1.90 60.39 0.37 59.72 0.34
12.71 1.59 19.31 1.03 16.15 0.93 7.66 0.97 10.95 0.22 11.61 0.20
3.78 0.91 4.41 0.54 14.79 0.93 43.93 1.84 6.00 0.15 7.47 0.16
36.98 2.50 16.65 1.16 6.09 0.67 3.71 0.69 22.65 0.34 21.20 0.30

62.55 2.41 52.80 1.44 27.78 1.32 4.74 0.96 69.69 0.35 64.53 0.33
7.56 1.48 9.45 0.89 4.42 0.57 0.42 0.20 3.51 0.14 3.87 0.14
5.98 1.06 6.71 0.67 39.55 1.44 88.75 1.23 15.58 0.26 18.34 0.26
12.49 1.73 7.93 0.72 5.64 0.65 3.59 0.55 10.21 0.24 9.70 0.22
11.42 1.42 23.10 1.28 22.60 1.20 2.50 0.61 1.01 0.09 3.57 0.13


Top five major impairments (n =
I I,169)t :
Back or neck problem (n = 2109) 14.78 1.86 27.80 1.36 16.98 1.21 8.19 0.99
Eye/Vision problem (n = 321) 7.43 1.48
Arthritis/rheumatism (n = 1766) 5.53 1.09 10.35 0.85 19.92 1.21 26.27 1.81
Fractures, bone or joint (n = 1033) 12.23 2.01 I 1.03 1.02 8.52 0.87 8.46 1.05
Lung problem (n = 913) 13.32 1.72 6.32 0.67 9.58 0.98
Walking problem (n = 838) 4.64 0.62 11.90 1.34
Heart problem (n = 873) 1 1.10 0.97 I 1.02 1.25


t The top five impairments or conditions selected on 1998-2000 BRFSS Disability/HRQOL module; Respondents were allowed to select from 14
major impairments or conditions, including "other" (n = 2232) for impairments or conditions not listed.
BRFSS = Behavioral Risk Factor Surveillance System, sd = standard deviation, HS = high school, SE = standard error




age at onset groups. The early onset group was younger on education, marital status, and employment, each of the
average and more likely to be male, employed, and more adult onset groups was significantly more likely to report
educated compared to the later onset groups. fair/poor health compared to the early onset group. The
following variables also showed a significant relationship
Table 2 provides the final adjusted parsimonious model with fair/poor health: age; African American race/ethnic-
of disability onset and fair/poor health. When controlling ity; less than high school education; divorced/separated
for current age, disability duration, gender, race/ethnicity, marital status; and not currently being employed. No sig-



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45-64


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Table 2: Model of Predictors of fair/poor general health from the 1998-2000 BRFSS*


Variables


Adjusted OR


95% Cl


Age at Onset:


Age:
Duration:
Gender:

Race/ethnicity:



Education:

Marital Status:




Employment Status:


0-21
22-44
45-64
>65
(per year increase)
(per year increase)
Male
Female
White, non Hispanic
Black, non Hispanic
All Hispanic
Other
> High school graduate
< High school graduate
Married/unmarried
couple
Divorced/separated
Widowed
Never Been Married
Employed
Unemployed
Student/homemaker
Retired
Unable to Work


*Logistic regression of BRFSS data are limited to 7 states & the District of Columbia and weighted with SPSS Complex Samples 14.0 unweightedd n
= 11,734; estimated weighted n = 12,895,725).
OR = Odds Ratio Cl = Confidence Interval; BRFSS = Behavioral Risk Factor Surveillance System


nificant association between disability duration and self-
reported fair or poor general health was observed after
adjusting for current age.

Discussion
This study represents the first major stride to consider the
relationship between different ages of disability onset and
self-reported general health of a broadly defined, sizeable
population of people with disabilities. While the BRFSS is
a cross-sectional survey, this study contains information
about a past "exposure" (disability onset) calculated from
information reported at the time of the interview. The
potential for recall bias regarding disability duration and
ultimately our measure of age at disability onset is an
inherent limitation of the data available. Given the cross-
sectional nature of the survey data and analyses, as well as
the reconstruction of prior disability onset, the causal
inference of our findings is limited.

In our descriptive analysis, early age at onset (age < 22
years) was associated with better health status. Our regres-
sion results also characterize individuals with an early
onset disability as reporting better general health than
people with later onset disability, even when controlling
for confounding variables, especially current age. These
results may support those of previous studies with more


homogeneous samples of specific impairments [10,16-
19] and are consistent with theoretical models on adapta-
tion to disability [ 12,13 ]; however, an alternative explana-
tion may be that health conditions that occur more
commonly in later life (e.g., arthritis, diabetes) may be
associated with both disability and decreased health sta-
tus. There are qualitative differences in many conditions
that give rise to disability in early life compared with those
that result in disability in later life. For instance, congeni-
tal conditions such as cerebral palsy may result in commu-
nication and ambulation limitations but not necessarily
poor self-defined and self-reported health. Based on these
findings, subsequent research should consider the timing
of disability in addition to the presence of disability. More
global examination of health status of people with disa-
bilities may mask differences associated with age at disa-
bility onset.

Future directions include investigation of early versus later
disability onset within specific conditions in a popula-
tion-based sample, as well as comparisons of social sup-
port and life satisfaction among disability onset groups. In
addition, the reasons for the association between age at
onset and self-perceived health status should be investi-
gated directly. Response shift is one theoretical reason for
the difference [15], however, there are no direct measures



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reference
1.52
1.67
1.53
1.02
1.00
reference
1.00
reference
1.22
1.01
0.75
reference
1.84
reference

1.39
1.02
0.99
reference
2.57
1.90
1.92
6.76


(1.37, 1.68)
(1.44, 1.94)
(1.26, 1.86)
(1.02, 1.02)
(0.99, 1.00)

(0.95, 1.05)

(1.15, 1.30)
(0.90, 1.14)
(0.69, 0.82)

(1.74, 1.95)


(1.32, 1.47)
(0.96, 1.09)
(0.92, 1.07)

(2.33, 2.83)
(1.75, 2.06)
(1.77, 2.09)
(6.29, 7.27)


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of response shift in the BRFSS. Future research may need
to examine this possible explanation, for example using
Rapkin and Schwartz's "appraisal" measure [31]. In an ad-
hoc analysis, we included life satisfaction as an indirect
proxy of differences in self-appraisal in our model and
found no appreciable changes (data available on request).
As with other possible mechanisms that will require more
detailed measurements, additional explanatory informa-
tion (e.g., social networks, disability identity) should be
used to further investigate age at onset differences.

These findings are subject to various limitations. The
BRFSS sampling frame excludes institutionalized adults,
restricting the inclusion of some individuals with severe
disability who may report poorer general health. The
phone survey methodology excludes people who are deaf
or hard of hearing and potentially some individuals with
severe mobility disabilities that limit their ability to
answer the phone [32]. In addition, participation in the
BRFSS, even among those sampled, has continued to
decline in tandem with the secular trends of research in
general [33]. Respondents from only seven states and the
District of Columbia were included in the analyses. While
the sample included respondents from the Eastern, South-
ern, and Midwestern regions of the country, these data
may not be fully representative of adults with disabilities
in the entire U.S. Furthermore, "disability" status and dis-
ability duration were determined by self-report and may
be prone to subjective interpretation of respondents. The
regression model did not control for limitation or impair-
ment type due to the multiple constructs contained within
the type of impairment question (impairments, diag-
noses/diseases, activity limitations, and injuries) and the
lack of response categories that were applicable to all
respondents; specifically, the difference in response pat-
terns between younger and older age at onset groups (see
table 1) leave a large response group of heterogeneous
conditions ("other") that differed across onset groups.
Lastly, as noted previously, the study was cross-sectional.
While we included age at onset as the prior historical
exposure, retrospective construction of a "cohort" of this
kind based on respondent recall data has inherent limita-
tions to cause and effect interpretations (i.e., the pseudo
cohort directly acts as a proxy based on the nature of this
sample being cross-sectional). This strategy allowed initial
examination of the relationship of age at onset and self-
reported health status for individuals with a wide range of
current ages and durations of disability, and provides sup-
port for future longitudinal studies to study these issues
prospectively.

Despite listed weaknesses, the BRFSS has many strengths
as a data source, including the population-based sampling
methodology. Disability was defined broadly, increasing
the generalizability of the results. The broad definition


may have attenuated the effect size, however, since the age
at onset relationship may be limited to subsets of people
with disabilities. The substantial sample size of the dataset
provided the ability to determine a moderate effect of age
at onset with statistical precision.

Conclusion
In this study, 23.3% of respondents with early onset disa-
bility reported having fair or poor health, while higher
proportions of respondents with later disability onset
reported fair/poor health. Despite adjusting for known
confounders (e.g., current age, education), age at onset
was significantly associated with reduced health status.
These findings suggest age at disability onset may impact
self-reported general health and should be considered
when analyzing HRQOL differences within people with
disabilities.

Competing interests
The authors) declare that they have no competing inter-
ests.

Authors' contributions
EWJ contributed to the design of the study and had pri-
mary responsibility for data analysis and manuscript
preparation. WHJ and VAC contributed to the study
design, data analysis, and manuscript preparation. RS and
EMA, contributed to the study design and participated in
manuscript preparation. This study grew out of work from
the REP, which provided valuable contributions toward
the preparation of this article. All authors have read and
approved the final manuscript.

Acknowledgements
The other members of the RRTC Expert Panel on Health Status Measure-
ment are: Phillip Beatty, Ph.D., NIDRR; Brad Cardinal, Ph.D., Ore-
gon State University; Charles Drum, Ph.D., Oregon Health & Science
University; Glenn Fujiura, Ph.D., University of Illinois at Chicago;
Trevor Hall, Ph.D., Oregon Health & Science University; Gloria Krahn,
Ph.D., Oregon Health & Science University; Margaret A. Nosek, Ph.D.,
Baylor College of Medicine. An earlier version of our findings was pre-
sented in March 2006 at the 23rd Annual BRFSS conference. Content from
this manuscript was originally presented to the Expert Panel on Health Sta-
tus Measurement of the Oregon Health & Science University Rehabilitation
Research and Training Center meeting in Portland, Oregon in June 2006.
This work was supported, in part, by the Rehabilitation Research and Train-
ing Center on Health & Wellness a grant from the National Institute on
Disability and Rehabilitation Research (NIDRR grant # H 133B040034) to
Oregon Health & Science University. Additionally, we'd like to thank
Babette Brumback, Ph.D. at the University of Florida Department of Epide-
miology and Biostatistics for time and assistance during this project. The
University of Florida, OHSU, and the CDC provided a supportive environ-
ment for this very important collaborative work to take place. The findings
and conclusions in this article have not been formally disseminated by the
Centers for Disease Control and Prevention and should not be construed
to represent any agency determination or policy.




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