Search PubMed⌕ Search

Biomedical subjects

E Stallard

Publications and source records attributed to E Stallard.

At least 55 records · Page 3Linked to original sources
PubMed1982

A cohort analysis of U.S. stomach cancer mortality 1950-1977.

Models of human carcinogenesis, such as the multi-stage model of Armitage and Doll, are designed to explain the age increase in the incidence of cancers in individuals. As a consequence, analyses of population level age-specific death rates via such models are appropriately applied to cohort data where such data are available. In this study a multi-stage model is applied to cohort data for stomach cancer death rates in the U.S. population for nine distinct cohorts observed over a recent 28-year period (1950-1977). The multi-stage model parameters obtained from the analysis of the cohort data show significant differences from the parameters obtained from analyses of cross-sectional mortality data under the assumption of no cohort differences in age-specific stomach cancer death rates.

Adult↗
PubMed1982

Bioactuarial models of national mortality time series data.

The incidence and prevalence of chronic degenerative disease in America's elderly population are important determinants of the need for long-term care health services. Though a wide range of data on disease incidence and prevalence is available from a variety of different health studies, a Congressional Budget Office study (1977) concluded that data limitations are a major factor in the lack of precise national long-term care cost estimates. In this paper, we present a modeling strategy to make better use of existing data by using biomedically motivated actuarial models to integrate multiple data sources into a comprehensive model of population health dynamics. The development of a specific model for application to a disease of interest involves three distinct phases. First, biomedical evidence and data are used to specify a cohort model of chronic disease morbidity and mortality. Second, the model is fitted to cohort mortality data with estimates of its parameters being derived by maximum likelihood procedures. Third, the morbidity distribution in the national population is generated from the parameter estimates. The model is used to examine lung cancer morbidity and mortality patterns for U. S. white and non-white males in 1977. A review of these patterns suggests that, based on current concepts of lung cancer incidence and natural history, over 2 percent of white males in the United States have lung cancer at some stage of development, though most of this prevalence is pre-clinical.

Actuarial Analysis↗
PubMed1982

The use of mortality time series data to produce hypothetical morbidity distributions and projects mortality trends.

It is difficult to obtain direct empirical estimates of chronic disease prevalence in the U.S. population. The available estimates are usually derived from epidemiological studies of selected populations. In this paper we present strategies for estimating morbidity distributions in the national population using auxiliary biomedical evidence and theory to estimate transitions to morbidity states from a cohort mortality time series. We present computational methods which employ these estimates of morbid state transitions to produce life table functions for both primary (morbidity) and secondary (mortality) decrements. These methods are illustrated using data on stomach cancer mortality for nine white male cohorts, aged 30 to 70 in 1950, observed for a 28-year period (1950 to 1977).

Adult↗
PubMed1982

Temporal trends in U. S. multiple cause of death mortality data: 1968 to 1977.

An analysis is made of the mortality trends over the period 1968 to 1977 indicated by two types of cause-specific mortality data. The first type of data is "underlying cause" of death data--the data heretofore used in national vital statistics reports on cause-specific mortality. The second type of data is "multiple cause" data which contain a listing of all medical conditions recorded on the death certificate. A comparison of trends in the two types of data yields useful insights on mortality declines over the study period for two reasons. First, these declines were largely due to a reduction in the mortality rates of circulatory diseases. Second, the multiple cause data contain considerably more information than the underlying cause data on the role of circulatory diseases, and many other chronic diseases, in causing death. This additional information is especially useful in examining mortality patterns among the elderly, where the prevalence at death of chronic degenerative diseases is high.

Actuarial Analysis↗
PubMed1981

Longitudinal models for chronic disease risk: an evaluation of logistic multiple regression and alternatives.

The logistic multiple regression model is often used in the analysis of the relation between chronic disease risk and selected risk factors in longitudinal data. Unfortunately, the logistic function has certain properties that make it inappropriate as a mode of risk analysis for longitudinal studies. The consequences of applying the logistic function to longitudinal data is that the numerical values of logistic regression coefficients cannot be meaningfully compared between studies of different durations. Sample calculations are presented to illustrate the magnitude of the problem for a range of relative study lengths and levels of risk. Two solutions are offered for the problem. First, a series of approximations are derived which permit such comparisons if the studies are not greatly dissimilar in length. Second, if comparisons of the risk coefficients are to be made across studies of greatly dissimilar duration, it is necessary to model risk via an appropriate statistical model. Criteria for assessing the appropriateness of risk functions for the analysis of longitudinal data are proposed and alternatives evaluated.

Chronic Disease↗
PubMed1981

A dynamic analysis of chronic disease development: a study of sex specific changes in coronary heart disease incidence and risk factors in Framingham.

An analysis of sex differentials in the dynamics of coronary heart disease (CHD) in the Framingham study is conducted using a methodology designed process which aids in the interpretation of the longitudinal results. This methodology permits the analysis of risk variable changes over time to be conducted independently of the analysis of the relation of risk variable values to CHD risk. The independent analyses afford a complete utilisation of information from longitudinal studies of chronic disease risk and produce insights into the dynamics of chronic disease development not available by other analytic strategies. The results of this analysis are compared with results obtained from a similarly structured multiple logistic analysis--a comparison which illustrates some of the technical and conceptual deficiencies of the often employed multiple logistic analysis when applied to longitudinal data.

Adult↗
PubMed1981

Methods for the analysis of mortality risks across heterogeneous small populations: examination of space-time gradients in cancer mortality in North Carolina counties 1970-75.

A method of analyzing mortality rates in heterogeneous populations is presented. This method, appropriate for the investigation of mortality rates in small geographic areas (e.g., counties) where the forces of mobility operate to selectively "package" person, is applied to the determination of whether a spatial west-east gradient in cancer mortality rates existed in North Carolina over the period 1970 to 1975. A significant gradient (as well as a significant temporal trend) is determined to exist in the data, though only for particular race, age and sex-specific demographic groups. Several alternate hypotheses are presented to explain the existence of the spatial gradient in these particular demographic groups.

Adult↗
PubMed1981

Methods for comparing the mortality experience of heterogeneous populations.

Methods are presented which produce Maximum Likelihood Estimates (MLE) of the degree of heterogeneity in individual mortality risks under a variety of assumptions about the age trajectory of those mortality risks. With these estimates of the degree of population heterogeneity it is possible to adjust comparisons of mortality risks across populations for the effects of population heterogeneity, differential mortality selection, and different age trajectories of the force of mortality. These methods are demonstrated by applying a variety of standard assumptions about the age trajectory of the force of mortality to the analysis of a broad range of cohort mortality data for the U.S. and Swedish populations. The estimates of the degree of heterogeneity, produced under all of the selected force of mortality models, consistently indicated a considerable degree of heterogeneity in mortality risks.

Adult↗
PubMed1981

A variance components approach to categorical data models with heterogeneous cell populations: analysis of spatial gradients in lung cancer mortality rates in North Carolina counties.

A mixed categorical-continuous variable model is proposed for the analysis of mortality rates. This model differs from other available models, such as weighted least squares and loglinear models, in that the within-cell populations are assumed to be heterogeneous in their levels of mortality risk. Heterogeneity implies that, in addition to the sampling variance considered in other available models, there will be a second component of variance due solely to within-cell heterogeneity. Maximum likelihood procedures are presented for the estimation of the model parameters. These procedures are based on the assumption that the distribution function for each cell death count is the negative binomial probability function. This assumption is shown to be equivalent to assuming a mixture of Poisson processes with the differential risk levels among individuals within each cell being governed by a two-parameter gamma distribution. The model is applied to data on lung cancer mortality for 1970-1975 for the 100 counties of North Carolina. The analysis shows that, though a gradient in lung cancer mortality rates exist in space, the gradient is restricted to specific demographic categories identified by race, age and sex.

Adult↗
PubMed1980

Population impact of mortality reduction: the effects of elimination of major causes of death on the 'saved' population.

In this paper we examine the effects on life expectancy of elimination of 4 major causes of death. Methodologically, we compare the results of cause elimination under assumptions of pattern of failure elimination and assumptions of underlying cause elimination in a modified multiple-decrement life table framework for the segment of the population impacted. The 4 diseases selected for analysis are cancer, ischaemic heart disease, stroke, and diabetes, major killers among the elderly population. The degree to which life expectancy changes occur within the population from elimination of a given cause if a function of 3 factors: 1) distribution of age at death by cause for persons who die of that cause, 2) the gain in person years lived for those 'saved' from dying from that cause which has been eliminated, and 3) the proportion of all deaths which are due to the specific cause which is eliminated. Mortality data from the 1969 U.S. multiple cause mortality tapes from NCHS are analysed to determine the impact of life expectancy for males and females of both races when one of these 4 specific causes of death is eliminated.

Adolescent↗
PubMed1980

A two-disease model of female breast cancer: mortality in 1969 among white females in the United States.

A mathematical model of the age distribution of breast cancer mortality was developed on the basis of the two-disease theory of breast cancer incidence. The model included representations of the time from tumor initiation to death, the competing risk effects of other disease, and differential susceptibility to each of the disease components. This model successfully predicted the single year of age frequency of breast canceomponents of this model was consistent with several epidemiologic findings. Most significantly, the age distribution of breast cancer deaths from premenopausal disease was consistent with incidence patterns in non-Western countries, where the incidence of the postmenopausal disease component was hypothesized to be lower because of nutritional differences.

Adult↗
PubMed1980

Estimates of U.S. multiple cause life tables.

Cause elimination life tables estimated from multiple cause of death data for four race/sex groups are presented for the U.S. population in 1969. These "multiple cause" life tables are then compared to cause elimination life tables where the mortality risk eliminated is that of the cause of death only in its occurrence as the underlying cause of death. An evaluation is made of the possible effects of the multiple cause data on our perception of the relative importance of the major causes of death. The reconceptualization of mortality risks made possible by the multiple cause of death data is also assessed in terms of its providing further insight into the "Taeuber paradox."

Adolescent↗
PubMed1980

Mortality of the chronically impaired.

An analysis of the effects of diabetes and generalized atherosclerosis on death due to ischemic heart disease or stroke was conducted using multiple cause mortality statistics. Specifically, all U.S. deaths in 1969 were classified into two groups on the basis of whether diabetes or generalized atherosclerosis was mentioned anywhere on the death certificate. Then race and sex specific analyses were made of ischemic heart disease deaths (or alternately of stroke deaths) using modified life table techniques for each group (one with the specified chronic disease and one without). Comparisons were made of mortality due to the acute circulatory events (ischemic heart disease or stroke) in the two groups to determine the implications of the chronic disease for the progression of the circulatory disease events. It was found, according to expectations, that diabetes and generalized atherosclerosis play very different roles in deaths due to stroke and ischemic heart disease.

Actuarial Analysis↗
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↗