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Biomedical subjects

E Stallard

Publications and source records attributed to E Stallard.

At least 19 recordsLinked to original sources
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

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↗
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↗
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↗
PubMed1979

A stochastic compartment model of stomach cancer with correlated waiting time distributions.

The incidence and growth rate of stomach cancer in the US population is modelled, for each sex, as a partially observed, discrete state stochastic process. Explicit evaluation of the transition rates between the states of the model is made possible by identifying them as specific functions of the time spent within each state. The functions used in the model were selected from the medical and epidemiological literature. With the model it was found possible to obtain fits to the age distribution of deaths due to stomach cancer for white males in 1975 and for selected age ranges for white females. These results suggested that the natural history of stomach cancer is different for females above and below age 65.

Adult↗
PubMed1979

Longitudinal analysis of the dynamics and risk of coronary heart disease in the Framingham Study.

Statistical methods designed specifically for the analysis of chronic disease incidence and progression in longitudinal studies are presented. These method model the risk of acute phases of chronic disease separately from the temporal change in risk variables. This could be accomplished because, under a specific biological model of the disease mechanism, the problems of estimating the risk of an acute event and of predicting the change in risk variables are independent. Specifically, a quadratic equation relating risk variable values to chronic disease risk and a system of linear equations predicting future risk variable values from present values may beestimated separately. Taken together, they utilize the full information available in a longitudinal study on the temporal dimension of chronic disease progression. In addition, the model is found to possess a number of attractive statistical and theoretical properties. These methods are applied to longitudinal data from the Framingham Study on coronary heart disease (CHD) in males. A quadratic function relating the risk of a CHD event to selected risk variables (age, and the natural logarithms of serum cholesterol, uric acid, diastolic blood pressure and pulse pressure) was estimated from measurements made at four points equally spaced in time (two years) with a further morbidity follow-up at a fifth point. The risk function was found to predict CHD risk accurately. It showed that, apart from the linear effects of the risk variables, cohort effects, quadratic effects and interaction effects were important predictors of CHD risk. The linear regression equations used to predict future risk variable values showed that there was an intricate network of cross-temporal associations. Study of the two types of equations jointly show that putative risk variables could affect the risk of CHD incidence both directly, by being associated with higher levels of risk, and indirectly, by causing other risk variable values to change with time. The results led us to identify several different roles that risk variables might play in CHD incidence.

Coronary Disease↗
PubMed1979

The impact of heterogeneity in individual frailty on the dynamics of mortality.

Life table methods are developed for populations whose members differ in their endowment for longevity. Unlike standard methods, which ignore such heterogeneity, these methods use different calculations to construct cohort, period, and individual life tables. The results imply that standard methods overestimate current life expectancy and potential gains in life expectancy from health and safety interventions, while underestimating rates of individual aging, past progress in reducing mortality, and mortality differentials between pairs of populations. Calculations based on Swedish mortality data suggest that these errors may be important, especially in old age.

Actuarial Analysis↗