Your Vegetables and Do Your Homework: A Design Investigation of

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Eat Your Vegetables and Do Your Homework: A Design Based Investigation of Enjoyment and Meaning in Learning Sasha Barab Anne Arid Craig Jackson Indiana University Design-based research is a collection of innovative methodological approaches that involve the building of theoretically-inspired designs to systematically generate and test theory in naturalistic settings. Design-based research is especially powerful with respect to supporting and systematically examining innovation. In part, this is due to the fact that conducting design-based research involves more than examining what is.

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NIH-PA Author Manuscript NIH-PA Author Manuscript NIH-PA Author Manuscript
NIH Public Access
Author Manuscript
J Gerontol A Biol Sci Med Sci. Author manuscript; available in PMC 2008 August 6.
Published in final edited form as:. 2008 June ; 63(6): 603–609.
A Physiologic Index of Comorbidity: Relationship to Mortality and
Disability
1,2 1 1 1Anne B. Newman , Robert M. Boudreau , Barbara L. Naydeck , Linda F. Fried , and Tamara
3B. Harris
1 Department of Epidemiology, Graduate School of Public Health, University of Pittsburgh, Pennsylvania
2 3 Department of Medicine, School of Medicine, University of Pittsburgh, Pennsylvania Laboratory for
Epidemiology, Demography and Biometry, National Institute on Aging, Baltimore, Maryland
Abstract
Background—In older adults, there is often substantial undiagnosed chronic disease detectable on
noninvasive testing, not accounted for by most comorbidity indices. We developed a simple
physiologic index of comorbidity by scoring five noninvasive tests across the full range of values.
We examined the predictive validity of this index for mortality and disability.
Methods—There were 2928 (mean age 74.5 years, 60% women, 85% white, and 15% black)
participants in the Cardiovascular Health Study (1992–1993) who had carotid ultrasound, pulmonary
function testing, brain magnetic resonance scan, serum cystatin-C, and fasting glucose. These were
combined into a single physiologic index of comorbid chronic disease on a scale of 0–10. Cox
proportional hazard models were used to predict mortality, mobility limitation, and activities of daily
living (ADL) difficulty after a maximum of 9 years.
Results—The range of the physiologic index was quite broad, with very few individuals having
total scores of either 0 or 10. Those with an index of 7–10 had a hazard ratio of 3.80 (95% confidence
interval, 2.82–5.13) for mortality compared to those with scores of 0–2, after adjustment for
demographics, behavioral risk factors, and clinically diagnosed conditions. Associations with
mobility limitation and ADL difficulty were also significant. The index explained about 40% of the
age effect on mortality risk.
Conclusion—Older adults with low levels of markers of chronic disease are rather rare but have
remarkably good health outcomes. The ability of such an index to distinguish usual from low risk
might provide an opportunity to better understand optimal health in old age.
Keywords
Disability; Mortality; Comorbidity
In older adults, chronic health conditions are quite common and are heterogeneous in patterns
of co-occurrence, duration, and severity (1). Indices of comorbid conditions have been
developed to account for overall disease burden when examining correlates and outcomes of
an index condition. For example, differences in mortality in patients with coronary artery
disease are largely explained by the extent of other concomitant morbid health conditions (2).
Many investigators have successfully used simple counts of the number of common chronic
Address correspondence to Anne B. Newman, MD, MPH, Professor of Epidemiology and Medicine, Director, Center for Aging and
Population Health, University of Pittsburgh, Graduate School of Public Health, 130 N. Bellefield Ave. Room 532, Pittsburgh, PA 15213.
E-mail: newmana@edc.pitt.edu.NIH-PA Author Manuscript NIH-PA Author Manuscript NIH-PA Author Manuscript
Newman et al. Page 2
conditions to summarize comorbidity (3,4). The Charlson Index is a more detailed method that
is notable for accounting for severity as well as number of conditions (4).
Most comorbidity indices are based on medical records, claims data (5), or self-report of a
physician diagnosis of disease, and thus represent clinically recognized comorbidity. It is well
known that, with advancing age, the prevalence of many common chronic diseases increases
markedly (3). Less well recognized is that chronic disease is often quite extensive well before
clinical diagnosis is made. In community-dwelling older adults who do not report disease, the
extent of subclinical disease can be substantial (6–9). Several epidemiologic studies have
incorporated noninvasive tests of disease to better quantify early pathology. For a number of
measures, such as vascular ultrasound, pulmonary function testing, and kidney function testing,
the extent of measurable disease in older adults has been shown to range from extremely low
levels to very high levels that can be as high as or higher than levels found in clinically
diagnosed patient populations (10–12). Although the term “subclinical” is often used to
describe this chronic disease pathology, it can be asymptomatic, presymptomatic, atypically
symptomatic, or simply undiagnosed. Regardless of the reason for a lack of clinical diagnosis,
such disease would not be counted in most clinical comorbidity indices. Because these
noninvasive tests detect such a wide range of disease in the “undiagnosed,” it is possible that
comorbidity assessment could be extended with noninvasive testing to further distinguish a
very high versus very low level of disease in a more continuous fashion than can be done by
using clinical diagnosis.
In the Cardiovascular Health Study (CHS), several of the most common chronic conditions
were assessed using noninvasive testing. Using these data, we developed a simple physiologic
index of comorbidity by scoring these tests across the full range of values. We examined the
predictive validity of this index for mortality as well as for disability. We hypothesized that
such an index might be a better determinant of risk than a clinical comorbidity index and would
better identify those at medium to low risk. We also examined whether a composite index of
these assessments might explain part of the contribution of age itself to risk.
Methods
Population
The CHS is an ongoing observational cohort study of cardiovascular risk in 5888 men and
women from four regions of the United States (13). The cohort was 65 years old or older at
enrollment in 1989–1990 and was supplemented with added minority recruitment in 1992–
1993. Participants and eligible household members were identified from a random sample of
Medicare enrollees at each field center. To be eligible, participants were 65 years old or older,
did not have cancer under active treatment, could not be wheelchair- or bed-bound in the home,
and did not plan to move out of the area within 3 years. We used data from the 1992–1993
examination to include all of the minority participants and to include the brain magnetic
resonance imaging (MRI) scan conducted at that time. Of 3660 individuals with a brain MRI
scan, a total of 2928 men and women had a clinical examination with complete data for the
other major components used in the analysis.
Physiologic Index of Comorbidity
The clinical examination conducted in 1992–1993 included cardiovascular and pulmonary
function tests, blood tests for kidney function and glucose tolerance, and a brain MRI. The
choice of tests used in the analysis was based on previous reports that each is individually an
important predictor of mortality (13,18), and that each represents a major, common age-related
chronic disease. Additional tests available in the CHS were considered, but were not assessed
at this same time point (bone density, e.g.). Others were nonspecific risk factors for mortality
J Gerontol A Biol Sci Med Sci. Author manuscript; available in PMC 2008 August 6.NIH-PA Author Manuscript NIH-PA Author Manuscript NIH-PA Author Manuscript
Newman et al. Page 3
(such as C-reactive protein or interleukin-6), that is, they were not measures of chronic disease.
Preliminary analyses confirmed that each was an independent predictor of mortality in the
CHS. All noninvasive tests had been obtained and examined independently and were not used
to diagnose or confirm clinical conditions.
Carotid ultrasound was obtained in the left and right internal and common carotid arteries to
assess near and far wall thicknesses and Doppler flow. The mean of the maximum of the internal
carotid artery was used in this analysis to represent the extent of atherosclerotic vascular disease
(14). Spirometry, including forced vital capacity (FVC) and forced expiratory volume in one
second (FEV1), was conducted using a water-sealed Collins Survey II spirometer (WE Collins,
Braintree, MA) according to the standards of the American Thoracic Society (13). Fasting
glucose levels were measured on a Kodak Ektachem 700 Analyzer (Ektachem Test
Methodologies, Eastman Kodak, Rochester, NY) and assayed within 30 days. Average monthly
coefficient of variation was 0.93% (15). Kidney function was assessed using a BNII
nephelometer (Dade Behring Inc., Deerfield, IL) that used a particle-enhanced
immunonephelometric assay (N Latex Cystatin-C) (16). Brain MRI was assessed on General
Electric or Picker 1.5-T scanners at three field centers and on a 0.35-T Toshiba instrument at
the fourth. The scanning protocol included a series of axial spin density, T - and T -weighted1 2
scans. Standardized sagittal T -weighted spin-echo images, axial spin density/T -weighted and1 2
T -weighted images were acquired, and scanned data were interpreted at a central MRI Reading1
Center by a neurologist trained in a standardized protocol (17). The white matter grade score
was used to indicate small-vessel vascular disease in the brain (18).
To construct the physiologic index of com