@article {1502, title = {Body mass index and mortality in nonsmoking older adults: the Cardiovascular Health Study.}, journal = {Am J Public Health}, volume = {88}, year = {1998}, month = {1998 Apr}, pages = {623-9}, abstract = {

OBJECTIVES: This study assesses the relationship of body mass index to 5-year mortality in a cohort of 4317 nonsmoking men and women aged 65 to 100 years.

METHODS: Logistic regression analyses were conducted to predict mortality as a function of baseline body mass index, adjusting for demographic, clinical, and laboratory covariates.

RESULTS: There was an inverse relationship between body mass index and mortality; death rates were higher for those who weighed the least. Inclusion of covariates had trivial effects on these results. People who had lost 10\% or more of their body weight since age 50 had a relatively high death rate. When that group was excluded, there was no remaining relationship between body mass index and mortality.

CONCLUSIONS: The association between higher body mass index and mortality often found in middle-aged populations was not observed in this large cohort of older adults. Over-weight does not seem to be a risk factor for 5-year mortality in this age group. Rather, the risks associated with significant weight loss should be the primary concern.

}, keywords = {Age Distribution, Aged, Body Mass Index, Cardiovascular Diseases, Cause of Death, Cohort Studies, Female, Humans, Logistic Models, Male, Mortality, Predictive Value of Tests, Risk Factors, Sex Distribution, Smoking, Survival Analysis, United States, Weight Loss}, issn = {0090-0036}, author = {Diehr, P and Bild, D E and Harris, T B and Duxbury, A and Siscovick, D and Rossi, M} } @article {1500, title = {Predicting future years of healthy life for older adults.}, journal = {J Clin Epidemiol}, volume = {51}, year = {1998}, month = {1998 Apr}, pages = {343-53}, abstract = {

Cost-effectiveness studies often need to compare the cost of a program to the lifetime benefits of the program, but estimates of lifetime benefits are not routinely available, especially for older adults. We used data from two large longitudinal studies of older adults (ages 65-100) to estimate transition probabilities from one health state to another, and used those probabilities to estimate the mean additional years of healthy life that an older adult of specified age, sex, and health status would experience. We found, for example, that 65-year-old women in excellent health can expect 16.8 years of healthy life in the future, compared to only 8.5 years for women in poor health. We also provide estimates of discounted years of healthy life and future life expectancy. These estimates may be used to extend the effective length of the study period in cost-effectiveness studies, to examine the impact of chronic diseases or risk factors on years of healthy life, or to investigate the relationship of years of life to years of healthy life. Several applications are described.

}, keywords = {Aged, Aged, 80 and over, Cost-Benefit Analysis, Female, Forecasting, Health Promotion, Health Status, Humans, Life Expectancy, Life Tables, Male, Probability, Quality-Adjusted Life Years, Sex Factors}, issn = {0895-4356}, author = {Diehr, P and Patrick, D L and Bild, D E and Burke, G L and Williamson, J D} } @article {1492, title = {Relationship between balance and abnormalities in cerebral magnetic resonance imaging in older adults.}, journal = {Arch Neurol}, volume = {55}, year = {1998}, month = {1998 Jan}, pages = {73-9}, abstract = {

BACKGROUND: Falling is a major cause of disability and morbidity among older adults. Because poor balance is a major reason for frequent falls, assessment of balance and its risk factors are important. In this study, we postulated that cerebral changes identified on magnetic resonance (MR) imaging are related to balance, and that older adults with balance problems would have significantly greater prevalence of such brain abnormalities than older adults without balance problems.

DESIGN AND MEASUREMENTS: Several measures of balance were examined in more than 700 community-dwelling older men and women, blacks and whites. Balance measures included dynamic posturography, functional reach, Romberg and 1-foot stand tests, tandem stand, and 1-foot stand. Cerebral MR imaging assessments included ventricular size, sulcal widening, white matter disease, and ischemic infarctions. Cardiovascular disease and hypertension were determined and controlled for in the analyses.

RESULTS: A summary of the balance measures was significantly related to each of the 4 MR imaging measures, with those with poorer balance having more disease. The strongest associations with balance were seen for white matter disease and ventricular size. All but the ischemic infarction variable remained significantly associated with balance after adjustments for sex, race, age, cardiovascular disease, and hypertension.

CONCLUSION: Cerebral changes identified by MR imaging are associated with poorer balance among older adults.

}, keywords = {Accidental Falls, Aged, Aging, Cerebral Cortex, Female, Humans, Magnetic Resonance Imaging, Male, Postural Balance, Risk Factors}, issn = {0003-9942}, author = {Tell, G S and Lefkowitz, D S and Diehr, P and Elster, A D} } @article {592, title = {Survival versus years of healthy life: which is more powerful as a study outcome?}, journal = {Control Clin Trials}, volume = {20}, year = {1999}, month = {1999 Jun}, pages = {267-79}, abstract = {

Studies of interventions that are intended to improve patients{\textquoteright} health are often evaluated with survival as the primary outcome, even when a measure adjusted for quality of survival, such as years of healthy life (YHL), would seem more appropriate. The purpose of this article is to determine whether studies based on survival are more or less powerful than studies based on YHL in clinical trials where either measure might be appropriate. We used data from the Cardiovascular Health Study (CHS) to estimate the sample size that would be needed in studies of 156 different health conditions, for the two outcome measures. The median sample size for a 5-year study was 687 if survival was the endpoint and 484 for YHL. YHL usually required lower sample sizes than survival, although survival was more powerful for some health conditions. We also found that lengthy studies, and studies with many follow-up measures per person, did not have appreciably higher power than less intensive studies. We conclude that clinical investigations in which the goal is to improve health may often be performed more efficiently with YHL rather than survival as the primary outcome measure. Such studies can be short in duration, with relatively few measures per person of health status.

}, keywords = {Aged, Angina Pectoris, Female, Follow-Up Studies, Health Status, Humans, Life Expectancy, Male, Quality-Adjusted Life Years, Randomized Controlled Trials as Topic, Research Design, Sample Size, Survival Analysis, Time Factors, Treatment Outcome}, issn = {0197-2456}, doi = {10.1016/s0197-2456(98)00062-2}, author = {Diehr, P and Patrick, D L and Burke, G L and Williamson, J} } @article {644, title = {Cluster analysis and patterns of findings on cranial magnetic resonance imaging of the elderly: the Cardiovascular Health Study.}, journal = {Arch Neurol}, volume = {58}, year = {2001}, month = {2001 Apr}, pages = {635-40}, abstract = {

OBJECTIVE: To characterize patterns of findings on cranial magnetic resonance imaging (MRI) of the elderly using a statistical technique called cluster analysis.

SUBJECTS AND METHODS: The Cardiovascular Health Study is a population-based, longitudinal study of 5888 people 65 years and older. Of these, 3230 underwent cranial MRI scans, which were coded for presence of infarcts and grades for white matter, ventricles, and sulci. Cluster analysis separated participants into 5 clusters based solely on patterns of MRI findings. Participants comprising each cluster were contrasted with respect to cardiovascular risk factors and clinical manifestations.

RESULTS: One cluster was low on all the MRI findings (normal) and another was high on all of them (complex infarcts). Another cluster had evidence for infarcts alone (simple infarcts), whereas the last 2 clusters lacked infarcts, one having enlarged ventricles and sulci (atrophy) and the other having prominent white matter changes and enlarged ventricles (leukoaraiosis). Factors that distinguished these clusters in a discriminant analysis were age, sex, several measures of hypertension, internal carotid artery wall thickness, smoking, and prevalent claudication before the MRI. The atrophy group had the highest percentage of men and the normal group had the lowest. Cognitive and motor performance also differed across clusters, with the atrophy cluster performing better than may have been expected.

CONCLUSIONS: These MRI patterns identified participants with different vascular disease risk factors and clinical manifestations. Results of these exploratory analyses warrant consideration in other populations of elderly people. Such patterns may provide clues about the pathophysiology of structural brain changes in the elderly.

}, keywords = {Aged, Brain, Cerebral Infarction, Cerebrovascular Disorders, Cluster Analysis, Cohort Studies, Discriminant Analysis, Female, Humans, Longitudinal Studies, Magnetic Resonance Imaging, Male, Risk Factors}, issn = {0003-9942}, doi = {10.1001/archneur.58.4.635}, author = {Longstreth, W T and Diehr, P and Manolio, T A and Beauchamp, N J and Jungreis, C A and Lefkowitz, D} } @article {634, title = {Patterns of self-rated health in older adults before and after sentinel health events.}, journal = {J Am Geriatr Soc}, volume = {49}, year = {2001}, month = {2001 Jan}, pages = {36-44}, abstract = {

OBJECTIVES: To describe and compare patterns of change in self-rated health for older adults before death and before and after stroke, myocardial infarction, congestive heart failure, cardiac procedure, hospital admission for cancer, and hip fracture.

DESIGN: "Event cohort," measuring time in months before and after the event.

SETTING: Four U.S. communities.

PARTICIPANTS: 5888 participants in the Cardiovascular Health Study (CHS), sampled from Medicare rolls and followed up to 8 years. Mean age at baseline was 73.

MEASUREMENTS: Self-rated health, including a category for death, assessed at 6-month intervals, and ascertainment of events.

METHODS: We examined the percentage that was healthy each month in the 5 years before death and in the 2 years before and after the other events, and compared the patterns to a "no event" group and to one another, using graphs and linear regression.

RESULTS: For people who died, health status declined slowly until about 9 months before death, when it dropped steeply. Comparing persons equally far from death, health was unrelated to age, but men and whites were healthier than women and blacks. Health for other events declined before the event, dropped steeply at the event, showed some recovery, and then declined further after the event. About 65\% to 80\% of the subjects were healthy 2 years before their event, but only 35\% to 65\% were healthy two years afterwards. Patterns were similar although less extreme for the "no event" group.

CONCLUSION: Visualizing trajectories of health helps us understand how serious health events changes health. Conclusions about change must be drawn with care because of a variety of possible biases. We have described the trajectories in detail. Work is now needed to explain, predict, and possibly prevent such changes in health.

}, keywords = {Aged, Cardiovascular Diseases, Cohort Studies, Death, Female, Follow-Up Studies, Health Status, Health Status Indicators, Hip Fractures, Hospitalization, Humans, Linear Models, Longitudinal Studies, Male, Random Allocation, Time Factors}, issn = {0002-8614}, doi = {10.1046/j.1532-5415.2001.49007.x}, author = {Diehr, P and Williamson, J and Patrick, D L and Bild, D E and Burke, G L} } @article {669, title = {Patterns on cranial magnetic resonance imaging in elderly people and vascular disease outcomes.}, journal = {Arch Neurol}, volume = {58}, year = {2001}, month = {2001 Dec}, pages = {2074}, keywords = {Aged, Brain, Cardiovascular Diseases, Cluster Analysis, Humans, Magnetic Resonance Imaging}, issn = {0003-9942}, doi = {10.1001/archneur.58.12.2074}, author = {Longstreth, W T and Diehr, P and Beauchamp, N J and Manolio, T A} } @article {673, title = {Probabilities of transition among health states for older adults.}, journal = {Qual Life Res}, volume = {10}, year = {2001}, month = {2001}, pages = {431-42}, abstract = {

GOAL: To estimate the probabilities of transition among self-rated health states for older adults, and examine how they vary by age and sex.

METHODS: We used self-rated health (excellent, very good, good, fair, poor, dead) collected in two longitudinal studies of older adults (mean age 75) to estimate the probability of transition in 2 years. We used the estimates to project future health for selected cohorts.

FINDINGS: These older adults were most likely to be in the same health state 2 years later, but a substantial proportion changed in both directions. Transition probabilities varied by initial health state, age and sex. Men were more likely than women to transition to excellent or dead. Women were more likely than men to transition to good or fair health. Although women aged 70 will have more years of life and more years of healthy life than men, they also have more years of unhealthy life, and the proportion of remaining life that is healthy is slightly higher for men. When observed and predicted years of healthy life (YHL) were compared in various subgroups, the YHL of persons with less favorable baseline characteristics was lower than predicted, and vice-versa. Differences, however, were small (about 5\%).

CONCLUSIONS: These transition probability estimates can be used to predict the future health of individuals or groups as a function of current age, sex, and self-rated health.

}, keywords = {Age Factors, Aged, Aging, Female, Health Status, Humans, Male, Probability, Quality of Life, Regression Analysis, Sex Factors}, issn = {0962-9343}, doi = {10.1023/a:1012566130639}, author = {Diehr, P and Patrick, D L} } @article {658, title = {Transforming self-rated health and the SF-36 scales to include death and improve interpretability.}, journal = {Med Care}, volume = {39}, year = {2001}, month = {2001 Jul}, pages = {670-80}, abstract = {

BACKGROUND: Most measures of health-related quality of life are undefined for people who die. Longitudinal analyses are often limited to a healthier cohort (survivors) that cannot be identified prospectively, and that may have had little change in health.

OBJECTIVE: To develop and evaluate methods to transform a single self-rated health item (excellent to poor; EVGGFP) and the physical component score of the SF-36 (PCS) to new variables that include a defensible value for death.

METHODS: Using longitudinal data from two large studies of older adults, health variables were transformed to the probability of being healthy in the future, conditional on the current observed value; death then has the value of 0. For EVGGFP, the new transformations were compared with some that were published earlier, based on different data. For the PCS, how well three different transformations, based on different definitions of being healthy, discriminated among groups of patients, and detected change in time were assessed.

RESULTS: The new transformation for EVGGFP was similar to that published previously. Coding the 5 categories as 95, 90, 80, 30, and 15, and coding dead as 0 is recommended. The three transformations of the PCS detected group differences and change at least as well as the standard PCS.

CONCLUSION: These easily interpretable transformed variables permit keeping persons who die in the analyses. Using the transformed variables for longitudinal analyses of health when deaths occur, either for secondary or primary analysis, is recommended. This approach can be applied to other measures of health.

}, keywords = {Aged, Data Interpretation, Statistical, Death, Decision Making, Female, Health Status, Humans, Logistic Models, Longitudinal Studies, Male, Models, Statistical, Quality of Life, ROC Curve, Surveys and Questionnaires}, issn = {0025-7079}, doi = {10.1097/00005650-200107000-00004}, author = {Diehr, P and Patrick, D L and Spertus, J and Kiefe, C I and McDonell, M and Fihn, S D} }