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Medical Biomathematics and Biometrics Commons™
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- Methodology (23)
- Evggfp exc/vgood/good/fair/poor/(dead) self-rated health (20)
- Cardiovascular Health Study (CHS) (17)
- Health Status and Years of Healthy Life (15)
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- Healthy life expectancy (2)
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- Small area variation (2)
- Age (1)
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Articles 1 - 30 of 49
Full-Text Articles in Medical Biomathematics and Biometrics
Comparing Years Of Healthy Life, Measured In 16 Ways, For Normal Weight And Overweight Older Adults, Paula Diehr
Comparing Years Of Healthy Life, Measured In 16 Ways, For Normal Weight And Overweight Older Adults, Paula Diehr
Paula Diehr
Introduction. The traditional definitions of overweight and obesity are not age specific, even though the relationship of weight to mortality is different for older adults. Effects of adiposity on aspects of health beside mortality have not been well investigated. Methods. We calculated the number of years of healthy life (YHL) in the 10 years after baseline, for 5,747 older adults. YHL was defined in 16 different ways. We compared Normal and Overweight persons, classified either by bodymass index (BMI) or by waist circumference (WC). Findings. YHL for Normal and Overweight persons differed significantly in 25% of the comparisons, of which …
Social Marketing, Stages Of Change, And Public Health Smoking Interventions, Paula Diehr
Social Marketing, Stages Of Change, And Public Health Smoking Interventions, Paula Diehr
Paula Diehr
As a "thought experiment," the authors used a modified stages of change model for smoking to define homogeneous segments within various hypothetical populations. The authors then estimated the population effect of public health interventions that targeted the different segments. Under most assumptions, interventions that emphasized primary and secondary prevention, by targeting the Never Smoker, Maintenance, or Action segments, resulted in the highest nonsmoking life expectancy. This result is consistent with both social marketing and public health principles. Although the best thing for an individual smoker is to stop smoking, the greatest public health benefit is achieved by interventions that target …
Health Benefits Of Increased Walking For Sedentary, Generally Healthy Older Adults: Using Longitudinal Data To Approximate An Intervention Trial, Paula Diehr
Paula Diehr
BACKGROUND: Older adults are often advised to walk more, but randomized trials have not conclusively established the benefits of walking in this age group. Typical analyses based on observational data may have biased results. Here, we propose a "limited-bias," more interpretable estimate of the health benefits to sedentary healthy older adults of walking more, using longitudinal data from the Cardiovascular Health Study. METHODS: The number of city blocks walked per week, collected annually, was classified as sedentary (<7 blocks per>week), somewhat active, or active (>or=28). Analysis was restricted to persons sedentary and healthy in the first 2 years. In Year …
Prevalence, Incidence, And Persistence Of Major Depressive Symptoms In The Cardiovascular Health Study, Stephen M. Thielke Md, Ms, Paula Diehr Phd
Prevalence, Incidence, And Persistence Of Major Depressive Symptoms In The Cardiovascular Health Study, Stephen M. Thielke Md, Ms, Paula Diehr Phd
Paula Diehr
PURPOSE: To explore the association of major depressive symptoms with advancing age, sex, and self-rated health among older adults. DESIGN AND METHODS: We analyzed 10 years of annual assessments in a longitudinal cohort of 5888 Medicare recipients in the Cardiovascular Health Study. Self-rated health was assessed with a single question, and subjects categorized as healthy or sick. Major depressive symptoms were assessed using the Center for Epidemiologic Studies Short Depression Scale, with subjects categorized as nondepressed (score < 10) or depressed (> or =10). Age-, sex-, and health-specific prevalence of depression and the probabilities of transition between depressed and nondepressed states were estimated. RESULTS: The …
Identification Of Ovarian Cancer Symptoms In Health Insurance Claims Data., Paula Diehr, Sean Devlin
Identification Of Ovarian Cancer Symptoms In Health Insurance Claims Data., Paula Diehr, Sean Devlin
Paula Diehr
Background: Women with ovarian cancer have reported abdominal=pelvic pain, bloating, difficulty eating or feeling full quickly, and urinary frequency=urgency prior to diagnosis. We explored these findings in a general population using a dataset of insured women aged 40–64 and investigated the potential effectiveness of a routine review of claims data as a prescreen to identify women at high risk for ovarian cancer. Methods: Data from a large Washington State health insurer were merged with the Seattle-Puget Sound Surveillance, Epidemiology and End Results (SEER) cancer registry for 2000–2004. We estimated the prevalence of symptoms in the 36 months prior to diagnosis …
Weight, Mortality, Years Of Healthy Life, And Active Life Expectancy In Older Adults, Paula Diehr
Weight, Mortality, Years Of Healthy Life, And Active Life Expectancy In Older Adults, Paula Diehr
Paula Diehr
OBJECTIVES: To determine whether weight categories predict subsequent mortality and morbidity in older adults. DESIGN: Multistate life tables, using data from the Cardiovascular Health Study, a longitudinal population-based cohort of older adults. SETTING: Data were provided by community-dwelling seniors in four U.S. counties: Forsyth County, North Carolina; Sacramento County, California; Washington County, Maryland; and Allegheny County, Pennsylvania. PARTICIPANTS: Five thousand eight hundred eighty-eight adults aged 65 and older at baseline. MEASUREMENTS: The age- and sex-specific probabilities of transition from one health state to another and from one weight category to another were estimated. From these probabilities, future life expectancy, years …
The Number Of Sick Persons In A Cohort, Paula Diehr
The Number Of Sick Persons In A Cohort, Paula Diehr
Paula Diehr
To see if the number of sick persons in a cohort was approximately constant over time, we calculated the number of sick persons in a “research” cohort of older adults followed for up to 14 years, and also in a synthetic birth cohort. Methods: In the research cohort, we calculated the actual number of persons in each health state over time, using eight different definitions of “sick”. For the birth cohort, we estimated the number of sick persons each year after birth. Results: The number of sick persons in the research cohort was approximately constant for 14 years, for all …
Age-Specific Prevalence And Years Of Healthy Life In A System With 3 Health States, Paula Diehr
Age-Specific Prevalence And Years Of Healthy Life In A System With 3 Health States, Paula Diehr
Paula Diehr
Consider a 3-state system with one absorbing state, such as Healthy, Sick, and Dead. Over time, the prevalence of the Healthy state will approach an 'equilibrium' value that is independent of the initial conditions. We derived this equilibrium prevalence (Prev:Equil) as a function of the local transition probabilities. We then used Prev:Equil to estimate the expected number of years spent in the healthy state over time. This estimate is similar to the one calculated by multi-state life table methods, and has the advantage of having an associated standard error. In longitudinal data for older adults, the standard error was accurate …
Synchrony Of Change In Depressive Symptoms, Health Status, And Quality Of Life In Persons With Clinical Depression, Paula Diehr
Synchrony Of Change In Depressive Symptoms, Health Status, And Quality Of Life In Persons With Clinical Depression, Paula Diehr
Paula Diehr
BACKGROUND: Little is known about longitudinal associations among measures of depression, mental and physical health, and quality of life (QOL). We followed 982 clinically depressed persons to determine which measures changed and whether the change was synchronous with change in depressive symptoms. METHODS: Data were from the Longitudinal Investigation of Depression Outcomes (LIDO). Depressive symptoms, physical and mental health, and quality of life were measured at baseline, 6 weeks, 3 months, and 9 months. Change in the measures was examined over time and for persons with different levels of change in depressive symptoms. RESULTS: On average, all of the measures …
Accounting For Missing Data In End-Of-Life Research, Paula Diehr, Laura Lee Johnson
Accounting For Missing Data In End-Of-Life Research, Paula Diehr, Laura Lee Johnson
Paula Diehr
End-of-life studies are likely to have missing data because sicker persons are less likely to provide information and because measurements cannot be made after death. Ignoring missing data may result in data that are too favorable, because the sickest persons are effectively dropped from the analysis. In a comparison of two groups, the group with the most deaths and missing data will tend to have the most favorable data, which is not desirable. Results based on only the available data may not be generalizable to the original study population. If most of the missing data are absent because of death, …
Methods For Incorporating Death Into Health-Related Variables In Longitudinal Studies, Paula Diehr
Methods For Incorporating Death Into Health-Related Variables In Longitudinal Studies, Paula Diehr
Paula Diehr
BACKGROUND AND OBJECTIVES: Longitudinal studies of health over time may be misleading if some people die. Self-rated health (excellent to poor) and the SF-36 profile scores have been transformed to incorporate death. We applied the same approaches to incorporate death into activities of daily living difficulties (ADLs), IADLs, mini-mental state examination, depressive symptoms, blocks walked per week, bed days, the timed walk, body mass index and blood pressure. STUDY DESIGN AND SETTING: The Cardiovascular Health Study of 5,888 older adults, was followed up to 9 years. Mean age was 73 at baseline, and 658 had an incident stroke during follow-up. …
Reliability, Effect Size, And Responsiveness Of Health Status Measures In The Design Of Randomized And Cluster-Randomized Trials, Paula Diehr
Paula Diehr
BACKGROUND: New health status survey instruments are often described by their psychometric (measurement) properties, such as Validity, Reliability, Effect Size, and Responsiveness. For cluster-randomized trials, another important statistic is the Intraclass Correlation (ICC) for the instrument within clusters. Studies using better instruments can be performed with smaller sample sizes, but better instruments may be more expensive in terms of dollars, opportunity cost, or poorer data quality due to the response burden of longer instruments. METHODS: We defined the psychometric statistics in terms of a mathematical model, and examined the power of a two-sample test as a function of the test-retest …
The Relation Of Dietary Patterns To Future Survival, Health, And Cardiovascular Events In Older Adults, Paula Diehr
The Relation Of Dietary Patterns To Future Survival, Health, And Cardiovascular Events In Older Adults, Paula Diehr
Paula Diehr
BACKGROUND: There have been few long-term follow-up studies of older adults who follow different dietary patterns. METHODS: We cluster-analyzed data on dietary fat, fiber, protein, carbohydrate, and calorie consumption from the U.S. Cardiovascular Health Study (mean age=73), and examined the relationship of the dietary clusters to outcomes 10 years later. RESULTS: The five clusters were named "Healthy diet" (relatively high in fiber and carbohydrate and low in fat), "Unhealthy diet" (relatively high in protein and fat, relatively low in carbohydrates and fiber); "High Calorie," "Low Calorie," and "Low 4," which was distinguished by higher alcohol consumption. The clusters were strongly …
Imputation Of Missing Longitudinal Data: A Comparison Of Methods, Paula Diehr, Jean Mundahl Engels
Imputation Of Missing Longitudinal Data: A Comparison Of Methods, Paula Diehr, Jean Mundahl Engels
Paula Diehr
BACKGROUND AND OBJECTIVES: Missing information is inevitable in longitudinal studies, and can result in biased estimates and a loss of power. One approach to this problem is to impute the missing data to yield a more complete data set. Our goal was to compare the performance of 14 methods of imputing missing data on depression, weight, cognitive functioning, and self-rated health in a longitudinal cohort of older adults. METHODS: We identified situations where a person had a known value following one or more missing values, and treated the known value as a "missing value." This "missing value" was imputed using …
Trajectories Of Health For Older Adults Over Time: Accounting Fully For Death, Paula Diehr
Trajectories Of Health For Older Adults Over Time: Accounting Fully For Death, Paula Diehr
Paula Diehr
The process of healthy aging can best be described by plotting the trajectory of health-related variables over time. Unfortunately, graphs including data only from survivors may be misleading because they may confuse patterns of mortality with patterns of change in health. Two approaches for creating graphs that account for death in such situations are 1) to incorporate a category or value for death into the longitudinal health variable and 2) to measure time in years before death or some other event. The first approach has been applied to self-rated health (excellent to poor) and the 36-Item Short-Form Health Survey (SF-36). …
The Aging And Dying Processes And The Health Of Older Adults, Paula Diehr
The Aging And Dying Processes And The Health Of Older Adults, Paula Diehr
Paula Diehr
It is difficult to distinguish changes in health due to aging from those related to dying, because the two processes are highly related. Some potentially treatable conditions may mistakenly be dismissed as due to old age. The goal of this article was to examine the relationships of aging and of dying to changes in 10 health-related variables: self-rated health, depression, ADLs, IADLs, minimental state examination, body mass index, blocks walked per week, bed days, hospitalization, and walking speed (all coded so that higher values were better). We used longitudinal data from the Cardiovascular Health Study to estimate the changes in …
The Importance Of The Normality Assumption In Large Public Health Data Sets, Paula Diehr, Thomas Lumley
The Importance Of The Normality Assumption In Large Public Health Data Sets, Paula Diehr, Thomas Lumley
Paula Diehr
It is widely but incorrectly believed that the t-test and linear regression are valid only for Normally distributed outcomes. The t-test and linear regression compare the mean of an outcome variable for different subjects. While these are valid even in very small samples if the outcome variable is Normally distributed, their major usefulness comes from the fact that in large samples they are valid for any distribution. We demonstrate this validity by simulation in extremely non-Normal data. We discuss situations in which in other methods such as the Wilcoxon rank sum test and ordinal logistic regression (proportional odds model) have …
Weight-Modification Trials In Older Adults: What Should The Outcome Measure Be?, Paula Diehr
Weight-Modification Trials In Older Adults: What Should The Outcome Measure Be?, Paula Diehr
Paula Diehr
BACKGROUND: Overweight older adults are often counseled to lose weight, even though there is little evidence of excess mortality in that age group. Overweight and underweight may be more associated with health status than with mortality, but few clinical trials of any kind have been based on maximizing years of healthy life (YHL), as opposed to years of life (YOL). OBJECTIVE: This paper examines the relationship of body mass index (BMI) to both YHL and YOL. Results were used to determine whether clinical trials of weight-modification based on improving YHL would be more powerful than studies based on survival. DESIGN: …
Transforming Self-Rated Health And The Sf-36 Scales To Include Death And Improve Interpretability, Paula Diehr
Transforming Self-Rated Health And The Sf-36 Scales To Include Death And Improve Interpretability, Paula Diehr
Paula Diehr
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 …
Probabilities Of Transition Among Health States For Older Adults, Paula Diehr
Probabilities Of Transition Among Health States For Older Adults, Paula Diehr
Paula Diehr
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 …
Patterns Of Self-Rated Health In Older Adults Before And After Sentinel Events, Paula Diehr
Patterns Of Self-Rated Health In Older Adults Before And After Sentinel Events, Paula Diehr
Paula Diehr
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 …
Measuring The "Managedness" And Covered Benefits Of Health Plans, Paula Diehr, David Grembowski
Measuring The "Managedness" And Covered Benefits Of Health Plans, Paula Diehr, David Grembowski
Paula Diehr
STUDY AIMS: (1) To develop indexes measuring the degree of managedness and the covered benefits of health insurance plans, (2) to describe the variation in these indexes among plans in one health insurance market, (3) to assess the validity of the health plan indexes, and (4) to examine the association between patient characteristics and the health plan indexes. Measures of the "managedness" and covered benefits of health plans are requisite for studying the effects of managed care on clinical practice and health system performance, and they may improve people's understanding of our complex health care system. DATA SOURCES/STUDY SETTING: As …
Survival Versus Years Of Healthy Life; Which Is More Powerful As A Study Outcome?, Paula Diehr
Survival Versus Years Of Healthy Life; Which Is More Powerful As A Study Outcome?, Paula Diehr
Paula Diehr
Studies of interventions that are intended to improve patients' 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 …
Methods For Analyzing Health Care Utilization And Costs, Paula Diehr
Methods For Analyzing Health Care Utilization And Costs, Paula Diehr
Paula Diehr
Important questions about health care are often addressed by studying health care utilization. Utilization data have several characteristics that make them a challenge to analyze. In this paper we discuss sources of information, the statistical properties of utilization data, common analytic methods including the two-part model, and some newly available statistical methods including the generalized linear model. We also address issues of study design and new methods for dealing with censored data. Examples are presented.
Predicting Future Years Of Healthy Life For Older Adults, Paula Diehr
Predicting Future Years Of Healthy Life For Older Adults, Paula Diehr
Paula Diehr
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, …
Effect Size And Power For Clinical Trials Using Years Of Healthy Life As The Primary Endpoint, Paula Diehr
Effect Size And Power For Clinical Trials Using Years Of Healthy Life As The Primary Endpoint, Paula Diehr
Paula Diehr
Some clinical trials perform repeated measurements on patients over time, plot those measures against time, and summarize the results in terms of the area under the curve. If the measured variable is health status, the summary outcome is sometimes referred to as years of healthy life (YHL), or quality-adjusted life years (QALY). This paper investigates some theoretical and practical aspects of randomized trials designed to assess measures such as YHL. We first derived algebraic expressions for the effect size of YHL measures under several theoretical models of the treatment's effect on health. We used these expressions to examine how the …
Optimal Survey Design For Community Intervention Evaluations: Cohort Or Cross-Sectional?, Paula Diehr
Optimal Survey Design For Community Intervention Evaluations: Cohort Or Cross-Sectional?, Paula Diehr
Paula Diehr
Community intervention evaluations that measure changes over time may conduct repeated cross-sectional surveys, follow a cohort of residents over time, or (often) use both designs. Each survey design has implications for precision and cost. To explore these issues, we assume that two waves of surveys are conducted, and that the goal is to estimate change in behavior for people who reside in the community at both times. Cohort designs are shown to provide more accurate estimates (in the sense of lower mean squared error) than cross-sectional estimates if (1) there is strong correlation over time in an individual's behavior at …
Breaking The Matches In A Paired T-Test For Community Interventions When The Number Of Pairs Is Small, Paula Diehr
Breaking The Matches In A Paired T-Test For Community Interventions When The Number Of Pairs Is Small, Paula Diehr
Paula Diehr
There is considerable interest in community interventions for health promotion, where the community is the experimental unit. Because such interventions are expensive, the number of experimental units (communities) is usually small. Because of the small number of communities involved, investigators often match treatment and control communities on demographic variables before randomization to minimize the possibility of a bad split. Unfortunately, matching has been shown to decrease the power of the design when the number of pairs is small, unless the matching variable is very highly correlated with the outcome variable (in this case, with change in the health behaviour). We …
Including Deaths When Measuring Health Status Over Time, Paula Diehr
Including Deaths When Measuring Health Status Over Time, Paula Diehr
Paula Diehr
Measuring health status over time is problematic when some subjects die, because death does not have a defined value on most health status measures. This situation is different from the usual missing data problem because the health status of the dead is, in a sense, known. We examined eight strategies for incorporating deaths into such analyses using three health status measures taken from two data sets, after which we used computer simulation to explore more fully the effect of deaths. The strategies differed in the amount of influence given to the deaths, varying from none (deaths were discarded) to complete …
Who Enrolled In A State Program For The Uninsured: Was There Adverse Selection?, Paula Diehr
Who Enrolled In A State Program For The Uninsured: Was There Adverse Selection?, Paula Diehr
Paula Diehr
Managed care plans may hesitate to participate in programs for uninsured persons because they fear adverse selection, whereby only the sickest people or highest users would choose to join the program. We studied this issue in Washington State's Basic Health Plan, a demonstration program that provides subsidized health insurance for families earning less than 200% of the poverty level. We interviewed people in three counties who enrolled in the program, and compared them to people in the same counties who were eligible but did not enroll. There were substantial differences between enrollees and eligibles in education, age, income, employment, race, …