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E Stallard

Publications and source records attributed to E Stallard.

At least 37 records · Page 2Linked to original sources
PubMed1992

Projecting the future size and health status of the U.S. elderly population.

"A projection model based on a multivariate continuous state, stochastic process is presented. The model allows multiple time-varying covariates to be used so parameters can be estimated from time series information on health changes and mortality, and their interaction. Health changes are simulated by altering parameters controlling the age trajectory and diffusion of risk factor means, variances, and covariances....By increasing the information used in projections it may be possible to better (a) anticipate the state of health at extreme ages, (b) forecast changes in health at specific ages over time, (c) stimulate the effects of specific interventions, and (d) determine the sensitivity of outcomes to a range of interventions."

Adult↗
PubMed1992

Risk factor dynamics, mortality and life expectancy differences between eastern and western Finland: the Finnish Cohorts of the Seven Countries Study.

Prior studies have not accounted for male mortality being higher in east than west Finland. Efforts to identify the mechanisms producing higher mortality in the east, due primarily to cardiovascular diseases (CVD), initially focused on a search for new risk factors. An alternate approach is to examine the assumptions of the analysis. This was investigated using a model which described (a) changes in risk factors over time, (b) dependency of risk factor effects on age, and (c) interactions and nonlinear effects of risk factors on mortality. The model was applied to 25-year follow-up data from cohorts of eastern (N = 823) and western (N = 888) Finnish men using pulse pressure, diastolic blood pressure, body mass index, total cholesterol, vital capacity index, cigarette smoking, and heart rate as risk factors. At age 40, men in the west had a life expectancy 2.4 years higher. Of the difference 29% (0.7 years) was associated with area differences in risk factor means, variances, and their change with age. The remainder, 1.7 years, was associated with age differences in the relation of risk factor interactions to CVD mortality. Possible reasons for these differences, such as joint elevation of several risk factors inducing rapid progression of atherogenesis, are discussed. No significant area differences were observed for mortality from either cancer or other causes.

Adult↗
PubMed1992

Analysis of underwriting factors for AAPCC (adjusted average per capita cost).

The adjusted average per capita cost (AAPCC) formula is used to determine payment to health maintenance organizations (HMOs) by Medicare. The four original underwriting factors (i.e., age, sex, institutional status, and welfare status) for the AAPCC were calibrated from the Current Medicare Surveys for 1974-76. Those factors have been updated by various actuarial adjustments. Revised calculations of the AAPCC underwriting factors are presented using survey data from the 1984 National Long-Term Care Survey and expenditure data from the Medicare Part A and Part B bill files. Also examined is the effect on the underwriting factors of chronic functional disability, defined as having one or more chronic limitations in activities of daily living. Comparison of alternative underwriting factors is conducted by simulating the dollar impact on payment to HMOs for select enrollee populations.

Actuarial Analysis↗
PubMed1992

Demographics (1950-1987) of breast cancer in birth cohorts of older women.

The effects of screening on breast cancer mortality, incidence, and prevalence were investigated using a general forecasting and simulation model. First, a biologically motivated model of disease incidence and mortality was fit to the breast cancer mortality experience of 15 U.S. White female birth cohorts followed for a 38-year period. The model assumed that breast cancer was the result of two different diseases. The first, or "premenopausal" disease, tends to have strong associations with the family history of disease and to be histologically more aggressive. The second, "postmenopausal" disease, occurs at more advanced ages, is apparently less strongly linked to family history, and is less aggressive with different histological characteristics (e.g., positive estrogen receptor status). Those results were used to forecast the effects of screening on the stage at diagnosis to simulate a screening program which reduced late-stage diagnoses by 50%. This produced large reductions in breast cancer mortality--an impact larger for disease associated with late age of onset.

Aged↗
PubMed1991

Analyses of black and white differentials in the age trajectory of mortality in two closed cohort studies.

We examine the relationship of age to mortality in blacks and whites in two cohort studies, the 20-year follow-up of the Evans County, Georgia. Study population and the 25-year follow-up of the Charleston Heart Study population. We conducted analyses with two parametric forms of hazard models (Gompertz and Weibull) for total mortality experience and considered the fit of the two hazard models in each study both separately and with the data pooled. We evaluated the robustness of conclusions about differences in the age pattern of mortality for blacks and whites by comparing results from the two hazard models. Where the tests were non-nested, we used an information-based statistic (AIC) to compare the fit of the models to the data. Results were robust to the selection of the hazard function, that is both models provided evidence that mortality rates at younger ages were lower for white than black females but that mortality rates increased more rapidly with age for white females. The absolute differences and the differences in the rates of increase were in the same direction, but smaller, for males. Though both models represented the general features of mortality patterns, the information statistic suggested better performance of the Gompertz function. The Gompertz function was also less sensitive to the initial age of determination of mortality exposure.

Adult↗
PubMed1991

Should the presence of carcinogens in breast milk discourage breast feeding?

Pollutant chemicals are commonly found in human milk at levels that would prevent its sale as a commercial food for infants. The chemicals found most commonly are dichlorodiphenyl-dichloroethene, polychlorinated biphenyls, dieldrin, chlordane, heptachlor, and polychlorinated dibenzodioxins. In general, the regulatory levels for these chemicals have been set to prevent cancer in adult humans from lifetime exposure. We compared lives saved in the postneonatal period by breast feeding to the estimated excess cancer deaths attributable to the contaminants in breast milk. The results of this analysis suggest that only extreme levels of contaminants in breast milk represent more of a hazard than failure to breast feed, but clinical considerations in individual cases might override this conclusion. Our analysis depends on assumptions about how the chemicals might cause cancer in humans and on whether breast feeding prevents some postneonatal mortality. Noncarcinogenic hazards from chemical exposure, other hazards from breast feeding such as transmission of viruses, and benefits of breast feeding other than reduction in mortality were not considered.

Breast Feeding↗
PubMed1991

Cross-sectional estimates of active life expectancy for the U.S. elderly and oldest-old populations.

Estimates are made of active life expectancy for the U.S. elderly and oldest-old populations using data from the 1982 and 1984 National Long Term Care Surveys. In the calculation of active life expectancy a multivariate analysis of 27 measures of functioning was used to define scores to decompose total life expectancy by type and level of disability. These analyses showed significant differences in active life expectancy for males and females. Though a higher proportion of male life expectancy at age 65 was "active," females had larger absolute amounts of active life expectancy. By age 85, in contrast, males had a higher absolute amount of active life expectancy. In addition, calculations were performed with the disability associated with cognitive impairment eliminated in order to illustrate the sensitivity of active life expectancy to changes in morbidity.

Activities of Daily Living↗
PubMed1991

Assessment of spatial variation of risks in small populations.

Often environmental hazards are assessed by examining the spatial variation of disease-specific mortality or morbidity rates. These rates, when estimated for small local populations, can have a high degree of random variation or uncertainty associated with them. If those rate estimates are used to prioritize environmental clean-up actions or to allocate resources, then those decisions may be influenced by this high degree of uncertainty. Unfortunately, the effect of this uncertainty is not to add "random noise" into the decision-making process, but to systematically bias action toward the smallest populations where uncertainty is greatest and where extreme high and low rate deviations are most likely to be manifest by chance. We present a statistical procedure for adjusting rate estimates for differences in variability due to differentials in local area population sizes. Such adjustments produce rate estimates for areas that have better properties than the unadjusted rates for use in making statistically based decisions about the entire set of areas. Examples are provided for county variation in bladder, stomach, and lung cancer mortality rates for U.S. white males for the period 1970 to 1979.

Bias↗
PubMed1989

The propagation of uncertainty in human mortality processes operating in stochastic environments.

This paper presents a model describing how the uncertainty due to influential exogenous processes combines with stochasticity intrinsic to physiological aging processes and propagates through time to generate uncertainty about the future physiological state of the population. Variance expressions are derived for (a) the future values of the physiological variables under the assumption that external factors evolve under a linear stochastic diffusion process, and (b) the cohort survival functions and cohort life expectancies which reflect the uncertainty in the future values of the physiological variables. The model implies that a major component of uncertainty in forecasts of the physiological characteristics of a closed cohort is due to differential rates of survival associated with different realizations of the external process. This suggests that the limits to forecasting may be different in physiological systems subject to systematic mortality than in physical systems such as weather where the concepts of closed cohorts and of mortality selection have no simple analog.

Aging↗
PubMed1989

Empirical Bayes procedures for stabilizing maps of U.S. cancer mortality rates.

"The geographic mapping of age-standardized, cause-specific death rates is a powerful tool for identifying possible etiologic factors, because the spatial distribution of mortality risks can be examined for correlations with the spatial distribution of disease-specific risk factors. This article presents a two-stage empirical Bayes procedure for calculating age-standardized cancer death rates, for use in mapping, which are adjusted for the stochasticity of rates in small area populations. Using the adjusted rates helps isolate and identify spatial patterns in the rates. The model is applied to sex-specific data on U.S. county cancer mortality in the white population for 15 cancer sites for three decades: 1950-1959, 1960-1969, and 1970-1979. Selected results are presented as maps of county death rates for white males."

Age Factors↗
PubMed1987

Statistically adjusted estimates of geographic mortality profiles.

The spatial variation of site-specific cancer mortality rates at the county or state economic area level can provide a) insights into possible etiologic factors and b) the basis for more detailed epidemiologic studies. One difficulty with such studies, especially for rare cancer types, is that unstable local area rate estimates, resulting from small population sizes, can obscure the underlying spatial pattern of disease risk. This paper presents a methodology for producing more stable rate estimates by statistically weighting the local area rate estimate toward the experience at the national level. The methodology is illustrated by the analysis of the spatial variation of two cancer types, bladder and lung, for U.S. white males over the three decades 1950-79.

Age Factors↗
PubMed1986

Dependent competing risks: a stochastic process model.

Analyses of human mortality data classified according to cause of death frequently are based on competing risk theory. In particular, the times to death for different causes often are assumed to be independent. In this paper, a competing risk model with a weaker assumption of conditional independence of the times to death, given an assumed stochastic covariate process, is developed and applied to cause specific mortality data from the Framingham Heart Study. The results generated under this conditional independence model are compared with analogous results under the standard marginal independence model. Under the assumption that this conditional independence model is valid, the comparison suggests that the standard model overestimates by 4% the effect on life expectancy at age 30 due to the hypothetical elimination of cancer and by 7% the effect for cardiovascular/cerebrovascular disease. By age 80 the overestimates were 11% for cancer and 16% for heart disease. These results suggest the importance of avoiding the marginal independence assumption when appropriate data are available--especially when focusing on mortality at advanced ages.

Adolescent↗
PubMed1986

Compartment model approaches for estimating the parameters of a chronic disease process under changing risk factor exposures.

Compartment model approaches have been proposed for the analysis of the age incidence of specific types of cancer. These models represented the age increases in incidence as the result of a compound hazard function where individual level risks were described by the Weibull hazard function and where the population level hazard rate is a continuous mixture of the Weibull hazards. These formulations assumed that the mixing function, which described differences in risk due to different exposure histories, was constant after the age at which the model was first applied. In this paper we show how the mixing distribution can be allowed to change with time reflecting changing exposures. The model is fitted to U.S. lung cancer mortality data where for recent male cohorts there appear to be changing patterns of exposure possibly related to recent declines in male smoking. The implications for future lung cancer mortality trends in the United States are discussed.

Adult↗
PubMed1986

Alternative models for the heterogeneity of mortality risks among the aged.

The authors examine how sensitive the estimates of heterogeneity in the mortality risks in a population are to the choices of two types of function, "one describing the age-specific rate of increase of mortality risks for individuals and the other describing the distribution of mortality risks across individuals." U.S. data from published Medicare mortality rates for the period 1968-1978 are used to analyze total mortality among the aged. "In addition, national vital statistics data for the period 1950-1977 were used to analyze adult lung cancer mortality. For these data, the estimates of structural parameters were less sensitive to reasonable choices of the heterogeneity distribution (gamma vs. inverse Gaussian) than to reasonable choices of the hazard rate function (Gompertz vs. Weibull)."

Adult↗
PubMed1985

The black/white mortality crossover: investigation in a community-based study.

The black/white mortality crossover at about age 75, a result of lower white mortality rates at younger ages and lower black rates at the oldest ages, has been observed in U.S. vital statistics since 1900. Though a persistant observation in such data, its validity has been challenged by questions about census enumeration and age reporting on death certificates. Analyses of 20 years experience of all-cause mortality in the community-based Evans County Study using a Weibull model of age specific mortality rates showed a statistically significant black/white mortality crossover for both men (at age 73) and women (at age 85). The finding of a crossover in this longitudinally followed population is significant because the age reporting for both survivors and age at death for nonsurvivors were obtained in the study protocol and did not rely on age reporting either in census data or on the death certificate. Differences in the age and sex patterns of mortality between two populations living in the same geographic region are relevant to questions about the etiology of the major age-related chronic diseases as well as to topics of current interest in health care policy.

Adult↗
PubMed1985

U.S. cancer mortality 1950-1978: a strategy for analyzing spatial and temporal patterns.

There are a number of technical and statistical problems in monitoring the temporal and spatial variation of local area death rates in the United States for evidence of systematically elevated risks. An analytic strategy is proposed to reduce one of the major statistical concerns, i.e., that of identifying areas with truly elevated mortality risks from a large number of local area comparisons. This analytic strategy involves two stages. The first is a procedure for examining the entire distribution of local area death rates instead of simply selecting high risk "outliers." The second is the development of an analytic procedure to relate the temporal changes in the cross-sectional distribution of local area death rates to models of the disease process operating within the populations in those areas. The procedures are applied to data on cancer mortality for the 3050 counties (or county equivalents) of the United States over the period 1950 to 1978. A number of striking mortality patterns, both within the entire United States and within various regions and states, are identified. For example, perhaps the most persistent finding was that the risk increases in the death rates for respiratory cancer mortality were due to a "catching up" of nonmetropolitan county mortality rates with metropolitan area mortality rates.

Adult↗